Urban Science doi: 10.3390/urbansci10090535

Authors: Nisrine Mezher

Analytical categories traditionally used to describe urban complexity—boundaries, fragmentation, segregation, enclaves—tend to portray spatial divisions as stable entities, privileging discontinuity over the relational processes through which it is produced. This limitation is particularly evident in cities marked by prolonged political instability, overlapping governance, or accelerated transformation. This article proposes the socio-spatial interface as a relational analytical framework that reframes rather than replaces the notion of boundary, understood as a configuration through which spatial forms, everyday practices, institutional arrangements, power relations, and historical conditions interact. Drawing on Lefebvre, Massey, de Certeau, and Bourdieu, and adopting a situated epistemology informed by Wittgenstein and Rancière, the article develops a four-dimensional methodological framework—institutional arrangements, material configurations, everyday practices and mobilities, and representations/memories/affects—derived from a doctoral fieldwork combining institutional documents, observation, a mobility questionnaire, in-depth interviews, and mental mapping. The framework is applied to an emblematic corridor of Beirut, traversed by the former demarcation line and encompassing three survey sectors—Furn el-Chebbak, Ghobeiry, and Tarik el-Jdidé—showing how the framework reveals markedly different configurations of separation, hybridity, and negotiated proximity across the three interfaces. The article contributes a situated approach to territorial analysis capable of informing architectural and urban design without reducing urban complexity to fixed spatial classifications.

Urban Science doi: 10.3390/urbansci10090534

Authors: Elena Simina Lakatos Mustafa Hmoudah Andreea Loredana Rhazzali Anca Cristina Glavan Lucian Ionel Cioca Hande Barlin Abdullah Altun Pinar Tat Halit Yanikkaya

The urban heat island (UHI) effect has become a persistent climate-related challenge affecting sustainable urban development, with consequences for public health, thermal comfort, energy demand, and climate adaptation. Numerous studies have investigated UHI using diverse observational, modeling, and analytical approaches. However, existing approaches remain fragmented and lack standardized integrated assessment frameworks. This study aims to synthesize the contemporary methodologies in UHI assessment and provide an integrated framework that supports sustainable urban heat mitigation and decision-making. A PRISMA-inspired systematic review was conducted using Web of Science (WoS) and considered peer-reviewed English-language articles published between 2016 and 2026. In line with the predefined inclusion and exclusion criteria, studies were screened and classified into several methodological domains: urban characterization, microclimate monitoring, urban environmental indicators, spatial analysis, statistical modeling, cooling interventions, and sustainable assessment. Based on the synthesized evidence, a proposed integrated methodological framework was developed, providing a comprehensive foundation for researchers, urban planners, and decision-makers to design standardized UHI studies and support climate-resilient and sustainable urban development.

Urban Science doi: 10.3390/urbansci10090533

Authors: Valeria Mammone Carmine Massarelli

Nature-based solutions (NBSs) are increasingly integrated into urban planning to enhance climate resilience and mitigate atmospheric pollution. However, the efficiency of urban forests is heavily dictated by the spatio-temporal dynamics of the selected plant species. This study proposes a conceptual and methodological framework to evaluate the potential contribution of deciduous and evergreen vegetation to urban pollution mitigation under different urban and environmental conditions. The framework considers seasonal vegetation dynamics and functional characteristics in relation to urban morphology, atmospheric conditions, and pollution sources, accounting for potential trade-offs between pollutant interception and air circulation. The proposed workflow integrates multi-temporal Earth Observation data, GIS-based spatial analysis, vegetation characterization, and atmospheric dispersion modelling. The proposed framework supports a context-sensitive evaluation of vegetation strategies for more adaptive and evidence-based urban green infrastructure planning.

Urban Science doi: 10.3390/urbansci10090532

Authors: Tsolmon Sodnomdavaa Hugejiletu Jin Mandakh Urtnasan Enkhbayar Davaatseren Erkhetbayar Enkhbayar Tegshjargal Sodnomdavaa Bayarsaikhan Sainbuyan

Urban monitoring in rapidly growing dryland cities is difficult because satellite signals and administrative records capture different aspects of settlement change and can perform differently across land-cover contexts. Mongolia provides a useful case because urban growth is concentrated in Ulaanbaatar while pastoral provinces remain exposed to ecological and livelihood shocks. We integrate MODIS NDVI, CHIRPS-derived SPI_12, a harmonized DMSP-OLS/VIIRS nighttime-light series, and administrative livestock and migration data for 22 spatial units over 2000–2024 (N = 550). A planned Landsat BuiltUp component was tested against Dynamic World for 2016–2024 (N = 39,600). The frozen NDBI > 0 and NDVI < 0.2 rule failed transfer validation (balanced accuracy = 0.474, Kappa = −0.052, F1 = 0.408; bare-to-built false-positive rate = 0.949), and enriched spectral models retained material province-specific errors. No repaired BuiltUp classifier was therefore frozen, and the original UEI, Mismatch, Ulaanbaatar M3, and spatial UEI analyses are not retained as principal evidence. In the retained origin-side panel, lower lagged NDVI anomaly is associated with greater livestock loss (β = −0.0148, p = 0.016), dzud severity with greater loss (β = 0.00454, p = 0.034), and higher prior-year livestock loss with higher standardized registered out-migration pressure (β = 1.113, p < 0.001). Nighttime-light harmonization shows strong level agreement but weaker rank continuity around the sensor transition. The study therefore advances a validation-first multi-source monitoring framework that withdraws unsupported urban composites after a failed measurement gate.

Urban Science doi: 10.3390/urbansci10090531

Authors: Juan José Saldarriaga González Pedro Moreno Diego Rossit Jesús del Carmen Peralta-Abarca Margarita Tecpoyotl-Torres Zakaryaa Zarhri

Municipal solid waste management remains a major challenge in intermediate cities because limited source separation, infrastructure constraints, and uneven citizen participation reduce system performance. Smart bins can support waste separation and operational monitoring. However, local implementation conditions are seldom systematically assessed before deployment. In this context, this article proposes a mixed-methods pre-implementation assessment that integrates documentary evidence, citizen perceptions, expert-informant perspectives, a conceptual IoT-enabled smart-bin architecture, and strategic analysis to inform a staged pilot in Cuernavaca, Mexico. The empirical component included a non-probabilistic convenience survey (n=253) and semi-structured interviews with five expert informants. The results showed that 15.4% of respondents reported prior familiarity with smart bins, whereas 79.8% perceived the technology as useful after a brief explanation, 68.4% expressed willingness to participate in a pilot, and 88.1% accepted brief training. Furthermore, economic incentives for waste separation were reported to motivate correct use by 75.9% of respondents; municipal service discounts were the preferred incentive, and 30.4% reported that they required no remuneration. Survey participants and expert informants identified financing, maintenance, vandalism, and institutional continuity as central implementation considerations. Overall, the present study provides context-specific evidence on how citizen openness and incentive preferences align with operational and institutional conditions, and it informs a staged pilot supported by environmental education, inter-institutional coordination, and systematic monitoring.

Urban Science doi: 10.3390/urbansci10090530

Authors: Abdulaziz I. Almulhim Haochen Shi

Virtual cities in video games have emerged as significant sites for the production and reinterpretation of contemporary urban imaginaries. By translating the complexity of real-world urban life into interactive and emotionally engaging environments, they offer new ways of experiencing and understanding cities. Despite their growing importance, research on virtual urbanism remains fragmented across disciplines and lacks a coherent conceptual foundation. Consequently, there is an urgent need for an integrative conceptual framework that explains how virtual cities mediate the production and transformation of urban knowledge. Drawing on an interdisciplinary synthesis of the literature from urban theory, media studies, and game design, this study identifies three key analytical dimensions (representation, abstraction, and spatial cognition) through which virtual urban experience is mediated, alongside urban rearticulation as a distinct process through which virtual urban experiences may be reinterpreted in relation to real urban thought and practice. These insights are integrated into the Virtual Urbanism Feedback Model (VUFM), a cyclical framework composed of three interconnected domains: Real to Virtual Inputs, Ludic Urban Transformations, and Virtual to Real Outputs. The model conceptualizes virtual cities as dynamic epistemic systems in which real and digital urban processes continuously interact through cycles of translation, reinterpretation, and feedback. The study contributes a unified conceptual framework for understanding digital urban mediation and highlights its implications for urban planning, urban design education, participatory planning, and the study of spatial experience in increasingly hybrid urban environments.

Urban Science doi: 10.3390/urbansci10090529

Authors: Evaristo Navarro Manotas Mario Alberto De La Puente Pacheco Hugo Hernández Palma Anderson Isaías Nieto Granados Mario Frank Pérez Pérez Angélica María Jiménez Coronado

This study examines the association between coastal climate pressure and labor market vulnerability in four Colombian Caribbean cities: Barranquilla, Cartagena, Santa Marta, and Riohacha. Using open-access secondary sources from DANE, IDEAM, UNGRD, INVEMAR, and DNP, the study constructs a 48-observation city-quarter analytical panel and estimates city and period fixed-effects models, distributed-lag specifications, and an event study design. A one-standard-deviation increase in climate pressure was associated with a 0.90 percentage point increase in informality (robust SE = 0.15, p < 0.001) and a 0.25 standard deviation increase in the composite labor vulnerability index (robust SE = 0.04, p < 0.001). The contemporaneous effect remained positive in the distributed-lag model, while the first lag was weaker and the second lag was not statistically distinguishable from zero. Emergency-quarter estimates also indicated a temporary increase in informality relative to the pre-event quarter. Taken together, the results provide empirical evidence consistent with a short-run relationship between hydrometeorological pressure and labor vulnerability in Colombian Caribbean coastal cities.

Urban Science doi: 10.3390/urbansci10090528

Authors: Valentina La Manna Alice Elizabeth González Pablo Gianoli-Kovar

Urban areas continue to grow steadily, leading to increases in vehicular traffic and urban noise levels, which may affect public health and quality of life. In this context, it is essential to develop tools capable of estimating and analyzing traffic-related noise. This work presents an update of the urban noise prediction model developed for Montevideo in 2000, incorporating new data obtained from the acoustic map of Montevideo 2024–2025 and recalibrating its parameters to current traffic conditions. To this end, variables such as traffic flow and composition, vehicle speed, and the presence of anomalous acoustic events (e.g., horns, braking, or modified exhaust systems) were analyzed. A statistical analysis of the recorded sound levels was also carried out to identify anomalous acoustic events and evaluate their influence on noise levels. Based on this analysis, correction factors related to these events and to traffic speed were incorporated into the model. The results show that the updated model improves predictive performance compared with the original formulation, reducing the percentage of errors outside the ±3 dBA range. Overall, the model constitutes a useful tool for estimating urban noise in Montevideo during daytime hours for traffic densities between 200 and 3000 veh/h, although challenges remain due to the high variability of the acoustic environment.

Urban Science doi: 10.3390/urbansci10090527

Authors: Apri Zulmi Hardi Alok Tiwari Ammar A. Naji

Coworking spaces have become an increasingly important component of contemporary urban economies, yet their spatial organisation remains poorly understood in rapidly developing Gulf cities. This study examines the spatial clustering and urban correlates of coworking space locations in Jeddah, Saudi Arabia. A dataset of 53 coworking spaces was integrated with points of interest, built-up land, and road-network data within a GIS framework. Spatial pattern was evaluated using Monte Carlo nearest-neighbour analysis, kernel density estimation, and Ripley’s L-function. A 1 km grid was subsequently used to model coworking space presence through binary logistic generalised linear regression, with a 2 km grid used for sensitivity analysis. Coworking spaces exhibited pronounced spatial clustering: the observed mean nearest-neighbour distance was 1023 m compared with 2667 m under complete spatial randomness (nearest-neighbour ratio = 0.384, Monte Carlo p = 0.001). The observed centred Ripley’s L-function exceeded the upper pointwise 95% CSR simulation envelope throughout the evaluated 0.25–10 km range, indicating multiscale spatial concentration. In the final 1 km model, business density (OR = 2.13, p < 0.001), built-up proportion (OR = 1.042 per percentage point, p < 0.001), and road density (OR = 1.075, p = 0.008) were positively associated with coworking space presence. Business density and built-up proportion remained significant at the 2 km scale, whereas the road-density association weakened. These findings suggest that coworking spaces in Jeddah are primarily embedded within business-intensive, highly urbanised, and accessible parts of the metropolitan area while also demonstrating sensitivity to spatial analytical scale.

Urban Science doi: 10.3390/urbansci10090526

Authors: Richard Penneigh Raj Bridgelall Joseph Szmerekovsky

Aggregate livability indices consistently rank Fargo, North Dakota, among the most livable small-to-mid-sized U.S. cities, yet city-level scores obscure whether favorable average performance reflects equitable neighborhood-level access to essential amenities. However, evidence on whether favorable citywide livability rankings correspond to equitable neighborhood-level access in small- and mid-sized U.S. cities remains limited. To address this gap, this study conducts a tract-level spatial accessibility analysis in Fargo, examining access to grocery stores, healthcare facilities, and parks across 38 census tracts using road network-based nearest-facility assignment, a Composite Accessibility Index (CAI), and Gini coefficients. Results reveal that despite strong aggregate rankings, approximately 9700 residents (8.0% of the study-area population of 121,219) reside in the bottom composite accessibility quartile. Standard Gini coefficients ranged from 0.081 to 0.093, while population-weighted Gini coefficients were lower (grocery = 0.040; healthcare = 0.042; parks = 0.029; CAI = 0.029), indicating modest citywide inequality. Nevertheless, the worst-served peripheral tract recorded a CAI of 0, with network distances ranging from 6.9 to 7.8 miles across the three amenity types. A sensitivity analysis confirms robustness across threshold choices. These findings indicate that modest citywide inequality can coexist with localized accessibility disadvantages in peripheral tracts, supporting spatially disaggregated, equity-oriented livability assessment.

Urban Science doi: 10.3390/urbansci10090525

Authors: Marek Pavlík Kamil Ševc

The rapid decarbonisation of urban districts is accelerating the deployment of rooftop photovoltaic (PV) systems, household battery energy storage systems (BESSs) and electric vehicles (EVs). However, the high variability of urban micro-generation creates substantial forecasting errors at the urban–grid interface, imposing high balancing costs on distribution system operators (DSOs) and local energy communities. Traditional metrics fail to assess how effectively internal peer-to-peer (P2P) flexibility offsets these forecast mismatches prior to grid settlement. To address this gap, this paper presents a novel methodological framework and a non-parametric indicator: the Community Imbalance Neutralisation Index (CINI). Formulated in a generalised, scalable matrix structure applicable to any heterogeneous urban neighbourhood (N households), CINI quantifies the relative reduction in net community-level imbalance relative to the cumulative sum of uncoordinated individual forecast errors. CINI ranges from 0 per cent (no collective mitigation) to 100 per cent (perfect internal neutralisation). Complementing this index, an adaptive day-ahead scheduling algorithm is introduced to determine the optimal community energy purchase requirement (Eforecast). The proposed framework is numerically evaluated using a high-resolution synthetic benchmark annual dataset with 15 min intervals (35,040 intervals) representing a Central European urban residential cluster equipped with diverse combinations of PV, BESS and managed EV charging infrastructure. The simulation results demonstrate that active cVPP coordination reduces annual grid-facing imbalance energy from 188.73 MWh to 143.88 MWh, increasing the annual CINI score from 57.22% to 67.39% (+10.17 percentage points) compared with the uncoordinated baseline. Notably, the framework reveals a ‘Winter Flexibility Paradox’, achieving its highest relative efficacy during the winter months (+13.88 percentage points in December). Furthermore, sensitivity analyses show that scaling flexibility up to 40 kW achieves a CINI score of 91.22%, revealing diminishing marginal returns and critical technological saturation thresholds. The proposed CINI metric and Eforecast dispatch algorithm provide city planners, municipal energy managers and DSOs with a transparent diagnostic tool to design dynamic socio-economic tariff incentives, optimise urban micro-grid sizing, prevent free-rider dynamics, and foster resilient, self-balancing smart cities.

Urban Science doi: 10.3390/urbansci10090524

Authors: Moundher Mouaki Benani Iasmina Onescu Cristina Alexandra Draghici

This paper examines the seismic vulnerability of historical buildings located in Lugoj City Center, an urban area of the Banat region in Western Romania, known for repeated earthquakes and rich architectural heritage. This research responds to the need for fast and practical means to help with the prioritization of risk mitigation and rehabilitation of historical cities, where detailed structural data are often limited. In light of the analysis of current European empirical, analytical, and hybrid techniques of seismic vulnerability assessment, this paper proposes a simplified empirical technique based on a systematic vulnerability index form. The suggested assessment comprises 42 indicators grouped in four weighted categories: structural aspects, architectural–artistic value, urban importance, and socio-economic importance. It is applied to 17 selected historical buildings of Lugoj City Center, including civil, religious, cultural, and infrastructural buildings. The assessment produced an average vulnerability index of 89.57, with 11 buildings classified as D1, 5 as D2, and 1 as D3, and an expected damage state under the VIII EMS-98 scenario. Thus, this study highlights the importance of combining seismic safety with heritage conservation and offers a flexible framework for urban-scale assessments, intervention planning, and preservation strategies in Lugoj and similar historic centers. This preliminary study represents the first phase of broader research addressing material degradation, monitoring, structural improvement, and socio-economic loss.

Urban Science doi: 10.3390/urbansci10090523

Authors: Pasit Rojradtanasiri Junko Tamura

The physical environment of a neighborhood, such as its road networks and land-use distribution, appears to be closely related to its ambient population density, but this relationship is difficult to measure quantitatively. A previous study based on Japanese neighborhoods addressed this challenge by developing an XGBoost baseline model to estimate Average Hourly Ambient Population Density (AHAPD) at a neighborhood scale using 16 physical environment-related features, achieving 75.9% accuracy. This study evaluates that baseline model by comparing it with human evaluators and multimodal AI models in a spatial reasoning task based on AHAPD estimation. A questionnaire-based benchmark with 29 sets of questions was developed to compare the three evaluator types across accuracy, reasoning, and confidence. The online questionnaire was distributed from 8 June–22 September 2025. In total, 100 responses were analyzed, comprising 94 human evaluators, 5 free-tier versions of multimodal AI models, and 1 output from the baseline model. The baseline model scored 16 points, compared with a mean of 15.1 points for the human evaluators and 14.2 points for the tested AI models. Its performance was also comparable to human evaluators with domain expertise and contextual familiarity, who averaged 16.0 points. The comparison further revealed differences in feature importance, confidence patterns, and characteristic errors among the evaluator types. Selected discrepancy cases highlighted possible strengths and weaknesses of each approach. The main contribution of this study is a questionnaire-based diagnostic benchmark for comparing evaluator types with different characteristics in spatial reasoning tasks.

Urban Science doi: 10.3390/urbansci10090522

Authors: Mousaab Alrhmoun Andrea Pieroni

Peri-urban belts are where most metropolitan residents actually meet farmland, and where urban food policy and agroecological transition physically overlap. They are also where wild food plants (WFPs) grow: on verges, ditch bank, and field margins, the interstitial biodiversity that complements cultivated crops. We ask whether the knowledge that makes those plants usable survives peri-urbanisation, and whether it can serve as a proxy for the resilience of the surrounding agroecosystem. Two Northern Italian landscapes with comparable perennial monoculture but opposite positions on the urban–rural gradient were compared through a diachronic design: the peri-urban lowland of the Trevigiano (Veneto), inside the dispersed-city fabric of the Venice–Padua–Treviso region and under rapid Prosecco expansion, and the Langhe (Piedmont), a UNESCO-listed hill district of low settlement density whose agriculture is nonetheless fully industrialised around wine grapes, hazelnuts, and tourism. Interviews with 74 informants were conducted through complementary designs: a cohort-structured approach in the Trevigiano and actor-diversified and diachronic interviews in the Langhe, recorded 13 folk food taxa in the Trevigiano against 43 in the Langhe (Jaccard 0.19). The peri-urban repertoire is thin and mostly inert: recognition survives while practice does not, with gaps of up to 86 percentage points between the two, and only Humulus lupulus, anchored in ritual, dialect, and a commercial product, is transmitted intact. The non-peri-urban repertoire is broader and still mobile, relocated by younger foragers onto unmanaged refugia and partly professionalised. The proxy, however, has a precondition. WFP knowledge indexes a healthy agroecosystem only where the land is clean enough to gather from, and the Trevigiano is not: informants avoid treated margins. The one EU instrument that would have banned pesticides in public green areas was withdrawn in 2024. We conclude that peri-urban planning should treat edges, unmanaged interstitial land, and treatment transparency as food-system infrastructure, and propose paired habitat and knowledge indicators for peri-urban agroecological assessment.

Urban Science doi: 10.3390/urbansci10090521

Authors: Yan Lu Bohan Wu Yu Eddie Hu Yi Izzy Jian Qian-Cheng Wang Yuefu Liu Zhaorong Feng

Dog ownership is rising quickly across dense Asian cities, coinciding with increasing competition for scarce urban green space. However, the cognitive factors associated with residents’ acceptance of human–dog shared park use remain poorly understood. Most existing evidence comes from low-density cities that rely on dedicated off-leash dog parks and therefore provides limited insight into dense, multi-use park systems where spatial segregation is difficult to implement. This study examines and tests a model of public acceptance of human–dog shared use in Shanghai, integrating the Stimulus–Organism–Response (S-O-R) paradigm with the Theory of Planned Behaviour (TPB). PLS-SEM was applied to 1045 cross-sectional intercept-survey responses collected across 229 parks in all 16 districts of Shanghai. Perceived risk and incivility were negatively associated with attitude toward shared use, whereas perceived social friction was not significantly associated with attitude. The two conflict constructs explained 12.5% of the variance in attitude. Attitude, subjective norm, and perceived behavioural control made positive and statistically significant formative contributions to the higher-order pro-sharing cognition composite (PSC). PSC was strongly and positively associated with acceptance intention (β = 0.796) and explained 63.3% of its variance. The findings suggest that acceptance intention is associated with a multidimensional pro-sharing cognitive orientation encompassing favourable evaluation, perceived social approval, and perceived manageability. Supplementary variance decomposition indicated that ATT, SN, and PBC made broadly balanced contributions to the model’s explanatory power. The study provides a locally adapted analytical framework for examining human–dog shared park acceptance and offers a basis for comparative research in other high-density cities.

Urban Science doi: 10.3390/urbansci10090520

Authors: Jose Luis Chavez-Torres Camila Nickole Fernandez-Morocho

Slope instability in urban road corridors can generate cascading effects on mobility, road safety, infrastructure functionality, and local response systems. This study assessed perceived urban vulnerability to landslide-related instability along the Vía de Integración Barrial corridor in Loja, Ecuador, using a hazard sources–exposed elements–response capacity framework. A cross-sectional perception-based survey was administered to corridor users and nearby actors. From 506 collected responses, 432 valid questionnaires were retained after informed-consent and attention-check screening. Categorical and ordinal data were analyzed using descriptive statistics, Wilson confidence intervals, grouped perception-based indicators, exploratory Spearman correlations, and selected chi-square contrasts with Cramér’s V. The results showed that perceived vulnerability was closely associated with visible signs of physical deterioration, including roadway cracking, pavement subsidence, soil or mud falls, and visible runoff or seepage. In addition, 81.5% of respondents perceived landslide-related disruption during the next rainy season as likely or very likely. The most frequently prioritized interventions were drainage improvement (62.3%), slope stabilization and retaining works (43.3%), and control of unwanted water inputs (41.2%). Institutional response was perceived as weak, slow, or mainly reactive by 80.3% of respondents, while low trust in reporting channels was reported by 54.9%; responses indicating lack of knowledge about the responsible institution or reporting channel were retained separately. Broad willingness to engage in community-based monitoring reached 89.4%. The exploratory bivariate analyses indicated a consistent pattern of positive associations among perceived disruption likelihood, mobility impact, road-safety concern, institutional response, and reporting trust, without implying formal validation of a latent multidimensional construct. This study provides an applied framework for incorporating user-based evidence into slope-risk management, corridor maintenance, road-safety planning, and resilience-oriented urban governance in mountainous cities.

Urban Science doi: 10.3390/urbansci10090519

Authors: C. Emilia Talamantes Carlos Salazar-Briones José Mizael Ruiz-Gibert Samantha Eugenia Cruz-Sotelo Hugo Favela-Avila Julio Cesar Juarez-Rodriguez

Rapid urban growth and increasing water stress in arid regions demand decentralized water management strategies. This study examines the potential for domestic greywater reuse in Mexicali, Mexico, through a multidimensional approach that integrates social perception, water quality, and institutional analysis to evaluate its viability in urban water transition processes. A structured survey was administered to 358 university students to identify consumption patterns and infrastructure using cluster analysis. This was complemented by physicochemical and microbiological characterization of raw greywater from domestic washing machines. Results indicate greywater generation rates of 170–176 L·capita−1·day−1 and high social acceptance of reuse. However, most raw water samples exceeded permissible regulatory limits for organic load and turbidity for non-potable uses, indicating a need for pretreatment. The study concludes that, despite volumetric feasibility and social support, persistent national regulatory gaps and institutional barriers constrain the formal adoption of these technologies. There is an urgent need to develop specific regulations and decentralized adaptive management policies tailored to the realities of arid urban contexts in the Global South.

Urban Science doi: 10.3390/urbansci10090518

Authors: Silvia Mangili Stefano Capolongo Andrea Rebecchi

Background: Artificial Light at Night (ALAN) is a growing public health concern, associated with circadian disruption, sleep disturbances, mental health issues, and increased risk for chronic conditions such as cancer and cardiovascular diseases. Despite a rapidly expanding epidemiological literature on ALAN-related health outcomes, there is limited consensus on standardized and comparable tools for assessing both how individuals perceive ALAN and their objective exposure at the individual and population levels. Methods: A scoping review was conducted using Scopus, PubMed, and Web of Science to identify studies published between 2010 and 2025. The aim was to systematically map the methods, tools, and frameworks used to evaluate both the perception of ALAN and objective ALAN exposure, and to examine their implications for public health. Eligibility was restricted to studies explicitly describing approaches to assess ALAN perception or exposure applied to human health research. Results: Most studies adopted cross-sectional designs and focused on urban contexts. Satellite-derived nighttime light data (62%) and GIS-based indicators (46%) were the most frequently used exposure proxies, while surveys and self-reported measures were commonly used to capture individual behaviors, health impacts and perceptions. Only 23% of studies employed wearable sensors or mobile applications, and architectural or building-level data were included in a single study (8%), highlighting a substantial gap in indoor exposure characterization. Conclusions: By critically reviewing current methods, tools, and frameworks, this work highlights the urgent need for harmonized, validated approaches that integrate objective environmental light measurements with human-centered data on how ALAN is perceived and experienced, thereby strengthening the evidence base for public health research and policy.

Urban Science doi: 10.3390/urbansci10090517

Authors: Sami Mujahed Jehad Abbadi Katja Tielbörger

Urbanization is one of many factors leading to global biodiversity declines due to its negative effect on habitat area, isolation, and quality. Green roofs have been proposed to mitigate adverse environmental effects by increasing local urban biodiversity and buffering the urban heat island effect. Nevertheless, little is known about the feasibility of green roof implementation in areas where it may be most needed, i.e., cities of the Global South where biodiversity is under pressure and where climatic and economic constraints may impede green roof establishment. Here, we aim to provide a proof-principle for the effectiveness of (low cost) wicking beds planted with native wild plant mixtures for increasing biodiversity in Hebron, West Bank. Effectiveness was evaluated in terms of establishment success and biodiversity of plants, and their potential to increase insect biodiversity compared to conventional roofs. Wild plants established in high densities and a decent rage of species. Green rooftops also supported significantly higher insect richness and abundance than conventional roofs. Our results highlight that green roof design with wild plants can be an effective and affordable means for urban biodiversity conservation in dry and hot areas.

Urban Science doi: 10.3390/urbansci10090516

Authors: Manel Mrabet Maha Sliti Muhammad Ismail Mohmand Atef Gharbi Dhouha Ben Noureddine

Urban services increasingly depend on interconnected sensing, communication, computing, decision-support, and response functions, yet technical performance alone does not establish service effectiveness. This structured integrative review examines WSNs, WBANs, V2X systems, 5G-enabled edge–cloud infrastructures, and prospective 6G capabilities across health, mobility, environmental monitoring, energy, water, infrastructure safety, and climate resilience. A five-database search covering January 2018–March 2025 was supplemented by citation tracing and a documented gap-directed update with a final cutoff of 1 July 2026. The analytical corpus comprised 40 peer-reviewed studies, five deployment cases, and one scope-boundary case. An outcome-mediated perception–network–edge/cloud–decision–response framework enabled categorical comparison of heterogeneous evidence without pooling non-comparable measures. Attribution was classified as T1 (comparatively evaluated downstream outcome), T2 (technical or bounded operational outcome), or T3 (conceptual linkage): three studies were T1, 34 T2, and three T3. Ten studies supported target-level SDG alignment, whereas none reached indicator-level correspondence. Evidence remained concentrated at communication, processing, decision-support, and bounded operational endpoints, with limited assessment of response availability and disruption–recovery conditions. Among the deployment cases, only SFpark supported T1 interpretation. These findings characterize the selected corpus and identify a persistent gap between technical performance and comparative, longitudinal, and distributionally assessed urban-service outcomes.

Urban Science doi: 10.3390/urbansci10090515

Authors: Nebojša Zdravković Mateja Zdravković Dalibor Nikolić Aleksandar Peulić

Urban traffic environments can elevate physiological stress, yet most existing studies assess this indirectly through infrastructural or traffic-related proxies rather than direct physiological measurement. This pilot study proposes a geographic information system (GIS)–Analytical Hierarchy Process (AHP) framework that integrates wearable heart-rate sensing with spatial analysis to identify localized physiological activation patterns at urban intersections. The proposed framework is presented as a methodological proof-of-concept and is not yet validated as a decision-support tool; application to urban health assessment or smart-city planning would require testing on a substantially larger and independently sampled spatial dataset. Data were collected from ten participants across 118 repeated commuting passes by private automobile at six intersections in Kragujevac, Serbia. An AHP-weighted urban stress index combining heart rate, the traffic-intensity proxy, time of day, and acceleration events (CR = 0.0115) was computed and mapped using inverse-distance-weighted interpolation. A linear mixed-effects model showed a significant positive association between an ordinal, time-of-day-based traffic-intensity proxy and heart rate across the 118 passes (8.90 bpm per ordinal unit, p < 0.001); because this proxy is derived from time-of-day categories, the association is best interpreted as an exploratory time-of-day–heart-rate relationship rather than a validated causal effect of traffic, and a sensitivity analysis confirmed that the same three intersections ranked highest across alternative weighting scenarios. The results indicate a consistent spatial relationship between intersections associated with higher traffic-intensity proxy values and elevated physiological activation. Although based on a limited pilot-scale dataset, the proposed framework demonstrates the feasibility of combining wearable physiological sensing with GIS–AHP spatial analysis and offers a methodological proof-of-concept for smart-city and urban-health research in medium-sized cities, pending validation on larger, independently sampled spatial datasets.

Urban Science doi: 10.3390/urbansci10090514

Authors: Diego Julián Rodriguez Patarroyo Jaime Francisco Pantoja Benavides Frank Nixon Giraldo Ramos

This research presents an integrated techno-energetic framework to decouple electric vehicle (EV) fleet growth from urban grid instability, using Bogotá, Colombia, as a case study. As emerging megacities confront rising charging demands, conventional reactive grid reinforcements are becoming technically and economically constrained. To address this, we develop a multi-layered optimization model that transforms urban Voronoi polygons into operational energy catchment units. Utilizing a Monte Carlo Tree Search (MCTS) algorithm, the framework determines infrastructure deployment sequences under two operational thresholds: a target high-resilience EV-to-charger ratio and a conservative scenario. Each localized node is technically dimensioned as a Representative Charging Station (RCS) equipped with a photovoltaic array and a Battery Energy Storage System (BESS). The results reveal spatial heterogeneity; high-density polygons in specific commercial and residential districts exhibit elevated infrastructure utilization alongside a stable solar resource baseline. Furthermore, the model demonstrates that this distributed architecture alleviates transformer thermal stress during the peak nocturnal charging period, mitigating localized overload risks and supporting distribution grid operational reliability. This study provides a scalable decision-making tool that bridges geospatial urban planning with renewable energy engineering to support the transition of constrained electrical networks.

Urban Science doi: 10.3390/urbansci10090513

Authors: Antonio Serra Olatz Irulegi-Garmendia Eva Vergara-Ruiz de Escudero Miriam Varela-Alonso Urtza Uriarte-Otazua

Outdoor environmental comfort is increasingly relevant amid climate change and population ageing because it affects well-being, behaviour and public-space use. However, the relationship between microclimatic conditions, environmental perception, and public-space use among older adults remains underexplored. The novelty of this study lies in integrating environmental measurements, subjective thermal perception, microclimatic simulations and public-space use within a baseline assessment undertaken before the redevelopment of a real public space, providing an evidence-informed framework for age-friendly urban design. The study examines environmental conditions, subjective perception and reported public-space use among adults aged 55 years and over within the Barrendain intervention area (Beasain, Spain). A mixed-method approach combined seasonal field surveys (n = 117) with microclimatic simulations. Survey data included thermal sensation, environmental perception, adaptive behaviour, and reported public-space use and perceived sociability. PET distributions were simulated using ENVI-met/BIO-met simulations driven by meteorological data from an official weather station. The results indicate that thermal perception exhibited a marked adaptive character. Neutral temperatures ranged from 12.35 °C in the cold-period campaign to 19.87 °C in the warm-period campaign, reflecting seasonal adaptive thermal responses among older adults. Tree-covered areas presented lower PET values than exposed surfaces during warmer conditions, highlighting the role of vegetation in mitigating summer heat stress. The partial correspondence between simulation-derived PET and subjective thermal sensation further emphasises the importance of combining objective microclimatic assessment with user-centred evaluation in age-friendly public-space design. In addition, 55% of respondents reported using the intervention area primarily for physical activity, whereas 36% identified social encounters as a main motivation for visiting the public space. The findings indicate that environmental comfort should be understood as an enabling condition for public-space use and perceived sociability rather than as their sole determinant. The proposed methodological framework demonstrates how simulation-based and user-centred evidence can be combined to support climate-responsive and age-friendly urban regeneration.

Urban Science doi: 10.3390/urbansci10090512

Authors: Zoi Christoforou Yeltsin Valero Nadir Farhi

Microvehicles, such as e-scooters and bicycles, are increasingly used in urban transport systems. Existing models were primarily developed either for pedestrians-only or motor vehicles-only and cannot fully capture the dynamics of microvehicles, particularly when they operate in shared spaces also used by pedestrians. This paper proposes a hybrid microscopic modeling framework for microvehicles’ and pedestrians’ trajectories based on a combination of physical interaction principles and deep learning techniques. A Long Short-Term Memory (LSTM) model is developed using space discretization and interaction variables to predict user trajectories in shared environments. The proposed framework was evaluated using observations collected through a semi-controlled experiment conducted at the University of Patras. Nearly 300 participants generated 553 trajectories involving pedestrians, bicycles, and e-scooters that were used for model calibration and validation. The model achieved satisfactory trajectory prediction accuracy with an RMSE below 0.20 m in testing scenarios. The model was compared to an adapted Social Force Model (SFM) for microvehicle and pedestrian interactions and showed better performance. The findings highlight important behavioral differences between pedestrians, bicycles, and e-scooters in terms of interaction distances and fields of view. The proposed framework can support future applications in infrastructure design, safety assessment, and traffic management.

Urban Science doi: 10.3390/urbansci10090511

Authors: Chulin Lu Yajun Cai Muchuan Xu

Metro station areas are transitioning from single-purpose transportation transfer nodes into multifunctional public spaces that integrate public services, cultural displays, and place-based experiences. However, there remains a lack of systematic evaluation tools for assessing public cultural service quality in metro station areas that integrate cultural meanings, public identity, and experiential expressions. An Analytic Network Process (ANP) network structure was established based on expert judgments to determine the weights, and Technigue for Order Preference by Similarity to Ideal Solution (TOPSIS) was applied for comprehensive evaluation and ranking using the scores provided by professional evaluators for 13 sampled stations in Foshan, Xi’an, and Shenzhen. Analytic Hierarchy Process (AHP)-TOPSIS was used for robustness testing, and dimensional weight perturbation analysis was conducted to assess model stability. Six types of Point of interests (POIs) were further incorporated to characterize the external functional contexts of the sampled stations. The results showed that the weights of Authenticity, Legitimacy, and Theatricality were 0.498, 0.296, and 0.206, respectively. Traditional, Self-expressive, Charismatic, Exhibitionistic, and Utilitarian were identified as the key indicators with relatively high weights. The 13 sampled stations showed significant differences in overall performance. Higher-performing cases demonstrated more balanced performance across the three scene dimensions of Authenticity, Legitimacy, and Theatricality. In contrast, lower-performing cases showed relatively weaker performance on some key indicators. The robustness test based on AHP-substituted weights and Spearman correlation analysis verified the stability of the evaluation framework, while the sensitivity analysis showed that the evaluation results remained relatively stable under weight perturbations. This study extends the application of scene theory in metro station area research and provides an evaluation framework and practical reference for optimizing public cultural service spaces in transit-oriented urban environments.

Urban Science doi: 10.3390/urbansci10090510

Authors: Mohamed Cherif Rahal

Existing readiness indices for Connected and Automated Vehicles (CAVs) produce a single composite score per city. This conflates use cases with very different territorial requirements and, being compensatory, allows strong performance on one criterion to mask a deficiency that is, in practice, a hard prerequisite. This paper proposes and demonstrates an assessment framework with four elements. First, the verdict is stratified by Operational Design Domain (ODD) profile, so that one territory yields one verdict per use case. Second, each profile is assessed only on its eligible service area, the roads on which the corresponding service could actually operate. Third, a non-compensatory veto layer is overlaid on a compensatory segment-level score, which separates the readiness score from the fit share, the proportion of network length that satisfies every critical threshold. Fourth, the diagnosis is extended to specific corridors through a readiness-aware routing formulation. The framework is demonstrated on the Versailles, Satory, and Velizy perimeter of about 92 square kilometes, using a real OpenStreetMap network of 4834 nodes and 733 kilometres, combined with an explicitly illustrative synthetic indicator calibration. Restricting each profile to its service area changes one verdict outright. The campus shuttle and urban robotaxi profiles obtain near-identical scores, both close to 0.51, but fit shares differing seven-fold, a distinction that a single score cannot express. Readiness-aware routing reroutes up to 42 percent of origin and destination pairs onto better-equipped itineraries for about 1 percent additional travel length. Monte Carlo analysis and cross-method tests using TOPSIS and PROMETHEE-II leave all verdicts unchanged. We position the work as a methodological demonstration rather than a validated deployment tool: the indicator values are synthetic, and empirical calibration, expert weight elicitation, and field validation remain prerequisites for operational use.

Urban Science doi: 10.3390/urbansci10090509

Authors: Yuqi Wang Zhixin Liu Paul Brindley

Urban canal-edge spaces are increasingly recognised as important blue–green infrastructure for mitigating urban heat; however, the mechanisms governing pedestrian thermal comfort in these environments remain insufficiently understood. This study employed a validated ENVI-met model to investigate the effects of canal orientation, canal width, water bodies and riparian tree configuration on pedestrian thermal comfort under summer heatwave conditions in Manchester, UK. A total of 32 scenarios were simulated to quantify the individual and combined effects of these design factors. Canal water alone provided only moderate daytime cooling, with its effectiveness depending strongly on canal orientation and local ventilation conditions. In contrast, riparian trees substantially improved thermal comfort through reductions in mean radiant temperature associated with canopy shading. Furthermore, the study identified that thermal performance was influenced not simply by the presence of blue and green infrastructure, but by their interaction. Rather than acting as the dominant cooling source, canal water enhanced the cooling effectiveness of adjacent vegetation, while continuous canopy shading emerged as the principal mechanism controlling pedestrian thermal comfort. These findings provide new insights into the mechanisms of canal-edge cooling and offer quantitative evidence to support climate-responsive design of thermally comfortable and resilient urban waterfronts.

Urban Science doi: 10.3390/urbansci10090505

Authors: Mustapha Adar Mohamed-Amine Babay Mustapha Mabrouki

The reliable long-term prediction of photovoltaic (PV) system performance is essential for optimizing operation, maintenance, and energy management in smart cities. Digital Twin (DT) technology has emerged as a promising approach for real-time monitoring and predictive analytics by continuously integrating physical system measurements with virtual models. However, many existing DT-based studies rely on limited validation periods, lack comprehensive uncertainty quantification, and provide insufficient comparisons with conventional forecasting approaches. To address these limitations, this study proposes a data-driven Digital Twin framework for daily photovoltaic energy production prediction for three silicon photovoltaic technologies (amorphous silicon, polycrystalline silicon, and monocrystalline silicon) operating under semi-arid climatic conditions in Morocco. The framework integrates data quality assessment and statistical production trend analysis based on linear regression, bootstrap confidence intervals, the Mann–Kendall trend test, and Sen’s slope estimator. In addition, the proposed DT model was benchmarked against persistence, linear regression, Random Forest, XGBoost, LightGBM, and Long Short-Term Memory (LSTM) models using a chronological training, validation, and independent testing framework. Model performance was evaluated over an independent test period of 602 consecutive days, representing approximately 1.65 years of continuous operation and more than one complete annual cycle. The proposed Digital Twin improved upon the standalone LightGBM model, achieving an RMSE of 1.3047 kWh/day, an MAE of 0.9255 kWh/day, a MAPE of 14.62%, and an R2 of 0.7015, compared with an RMSE of 1.3349 kWh/day, an MAE of 0.9637 kWh/day, and an R2 of 0.6875 for LightGBM. Over the 11-year monitoring period, the estimated long-term production trend rates were −0.566% yr−1 for a-Si, −0.335% yr−1 for pc-Si, and −0.260% yr−1 for mc-Si. Bootstrap analysis yielded median long-term production trend rates of −0.573, −0.326, and −0.251% yr−1, respectively, while Mann–Kendall tests indicated no statistically significant monotonic production trend for any technology (p = 0.1611, 0.2758, and 0.3502, respectively). The extended independent testing period, combined with statistical production trend analysis and comparative machine-learning evaluation, demonstrates the applicability of the proposed Digital Twin framework for photovoltaic performance monitoring and adaptive prediction under semi-arid climatic conditions.

Urban Science doi: 10.3390/urbansci10090508

Authors: Ricardo Almendra Catarina Ferrão Luisa Dias Pereira

Contemporary urban environments are characterized by intense and continuous activity, resulting in a significant transformation of the ambient acoustic environment. Noise pollution from sources such as traffic, construction, industry, and recreation propagate throughout these areas, although some residents may report a low perception of disturbance even under high exposure levels. This study investigates the moderating influence of housing conditions on the relationship between outdoor noise levels and perceived indoor acoustic environment in Coimbra, Portugal. The methodology combines primary data on housing characteristics and subjective indoor noise perception, obtained through a questionnaire survey, with secondary data from an environ-mental noise map. Logistic regression models, incorporating interaction terms, were employed to evaluate the moderating effect of housing conditions. The results demonstrate a statistically significant association between outdoor noise exposure and perceived indoor noise, with a limited moderating effect of housing conditions on this relationship.

Urban Science doi: 10.3390/urbansci10090507

Authors: Simao Alice Chen

In recent years, gentrification has frequently been linked to housing inequality and mass evictions and portrayed in a negative light. This study defines gentrification in terms of neighborhood median household income, income diversity, and their level and trajectories over 14 years (2010–2023), and classifies neighborhood gentrification stages using hierarchical clustering. It then adopts a quantitative, data-driven approach to examine the pairwise statistical and geospatial relationships among gentrification stages, executed evictions (2023–2024), and other housing characteristics (rent, socioeconomic status, and demographics) across New York City neighborhoods. The results demonstrate that pre-gentrifying neighborhoods were 39.08 times more likely to have eviction rates 1.5 standard deviations above the mean, 14.19 times more likely to be geospatial eviction hotspots, and three times more likely to experience evictions per neighborhood than fully gentrified neighborhoods. Income-adjusted regression models indicate that gentrification-stage membership explains variation in eviction severity beyond median household income alone, increasing explained variance from 27.9% to 42.6%; late-stage gentrifying and stable low-change neighborhoods showed significantly lower eviction severity than fully gentrified neighborhoods at comparable income levels. Spatially, the Bronx, the most economically disadvantaged borough, contained 11 of 17 eviction-outlier NTAs and 37 of 48 geospatial eviction hotspots, making it the most eviction-concentrated area in the city. This clustering-based classification framework relies only on widely available Census and administrative data and can be applied to other metropolitan areas or adapted to related urban domains such as land-use and zoning analysis. Targeted, actionable recommendations are offered to direct eviction-prevention resources toward the most vulnerable communities.

Urban Science doi: 10.3390/urbansci10090506

Authors: Salvatore Saporito

Recent advances in spatial data and routing algorithms allow researchers to define the areas surrounding individuals using network distance rather than Euclidean distance. These differently constructed local environments then serve as inputs to spatial segregation measures, with network-based environments often producing higher segregation values than comparable Euclidean-based environments. These differences are frequently interpreted as evidence that mobility barriers embedded in the built environment shape patterns of racial isolation. However, distance-based local environments constructed over road networks typically contain fewer people than those constructed using Euclidean distance, raising the possibility that observed differences may reflect variation in the population composition of local environments rather than mobility constraints alone. This methodological study evaluates that possibility by constructing spatial segregation measures from both distance-based and population-based (k-nearest-neighbor) local environments defined using network and Euclidean distance. Whereas distance-based local environments built using network distance systematically include fewer people than those constructed using Euclidean distance, population-based local environments hold the size of local populations constant across measurement approaches. Holding constant the population of local environments reveals that differences between segregation measures based on network and Euclidean distance are substantially reduced across most U.S. places, although meaningful differences remain in some places. These findings suggest that previously documented differences between network- and Euclidean-based spatial segregation measures may partly reflect differences in the number of people included in local environments due to network-constrained reach.

Urban Science doi: 10.3390/urbansci10090504

Authors: Wei-Tzu Hung Jen-Yang Lin Chi-Feng Chen

Urban heat islands in densely built cities pose growing risks to public health and energy demand. Urban parks are key nature-based solutions, yet empirical evidence on park cool island (PCI) effects intensity and extent in compact cities remains limited. This study evaluated PCI for 12 pocket-to-medium/large urban parks in central Taipei, Taiwan. Land surface temperature (LST), mean radiant temperature (MRT), and effective temperature (ET) were measured along transects from park interiors into surrounding areas and linked to local environmental conditions. Parks showed PCI intensity in LST with an average cooling of 4.23 °C and an average cooling of 0.3 °C in ET; MRT cooling was weaker and spatially inconsistent. The cooling of LST extended to about 60 m beyond the park’s edges, while the cooling of ET reached approximately 150 m. In addition, the results show that shade and relative humidity are significant factors affecting PCI, and pervious pavement and wind speed also contribute to cooling LST and ET. The field observations provide evidence that urban parks contribute cooling effects and might reduce the risk of heat hazards.

Urban Science doi: 10.3390/urbansci10090503

Authors: Antoine Lovell Earl J. Edwards Jennifer Daniels Tina Jordan

Housing insecurity is one of the most urgent social problems in the United States, with eviction filings reflecting an important dimension of housing instability. This paper analyzes 75 monthly Florida eviction-filing observations from January 2019 through March 2025 to examine whether filing trajectories changed during and after pandemic-era tenant protections. Guided by an institutional temporality framework, we used descriptive analyses, a policy-guided interrupted time-series (ITS) model with Newey–West/HAC inference, a Fourier-seasonal dynamic regression with autoregressive errors, and exploratory segmented regression. The filing numerator covers all 67 Florida counties. Counts were the primary outcome; a secondary author-calculated rate used a fixed denominator of 2,794,102 renter-occupied housing units from the 2019–2023 American Community Survey 5-Year Table B25003. Mean monthly filings were 10,766 before March 2020, 6551 during March 2020–June 2021, and 11,701 during July 2021–March 2025. The primary ITS estimated an immediate March 2020 decline of 6854 filings (95% CI: 4541–9166 fewer; p < 0.001); the preferred AR(2) dynamic model also supported a large March decline (5957 fewer; p = 0.011). The July 2021 immediate change and direct tests of a higher post-period trajectory were not statistically significant. Overall annual seasonality was supported, but the apparent January and October peaks were not significant after adjustment. Florida filings therefore fell sharply around the onset of pandemic protections and subsequently returned toward the historical range, without statistically credible evidence that the post-moratorium trajectory became higher than the pre-pandemic trajectory.

Urban Science doi: 10.3390/urbansci10090502

Authors: Marián Gogola Dominik Krčmár

Road safety is an important aspect of sustainable mobility in urban transportation, with excessive speed a primary contributor to the severity of traffic accidents. Monitoring it is a challenge for current transport systems; however, the current state of open data technologies allows for the collection, monitoring and analysis of traffic data using low-cost devices that can help local citizens verify and support their concerns about dangerous situations in specific areas. This study presents the results of speeding on various street segments in the city of Žilina, Slovakia, based on the data gathered from Telraam low-cost traffic sensors. Differences among the various locations were tested with nonparametric statistical tests (Kruskal–Wallis test and Dunn’s post hoc comparisons). The data provide insight into the largely passenger-car traffic at all sites and show significant variation in the proportions of bikes, pedestrians, and heavy vehicles. The particular differences in speeding behaviour in the spatial context were observed in some locations: Oslobodenia, Okruzna, and Zavodskeho showed the highest V85 values and increased proportions of vehicles exceeding 50 km/h, while Hviezdoslavova, Osvety, and Univerzitna showed substantially lower operating speeds. The findings indicate that some residential collector road segments record a higher share of overspeeding than the main road. Such findings suggest that low-cost devices may be useful technology to support citizens and their initiatives in a real way, enhancing road safety. The findings suggest that low-cost open-data sensors can support preliminary speed-management screening by identifying locations with elevated speeding indicators that warrant more detailed investigation.

Urban Science doi: 10.3390/urbansci10090501

Authors: Jingfang You Shuhao Zhong Dingji Zeng Tuo Zeng Jiaye Su Shengbin Yang Ming Zhong

Against the background of global climate change and rapid urbanization, the frequency of extreme hydrological events has increased markedly, and hydrological and geological hazards induced by extreme heavy rainfall have occurred frequently. Considering the joint occurrence characteristics of heavy rainfall hazards, statistical methods are used in this study to develop a mathematical model for calculating hazard–risk combinations and disaster-triggering thresholds that integrates copula functions and the Kendall return period. First, a bivariate joint-distribution probability model is established using copula functions. Then, the Kendall return period under the same recurrence level is calculated to infer combined hazard thresholds for multiple disaster-causing factors. Taking rainfall-induced flash floods and landslides as examples, combined hazard thresholds are calculated. Rainfall and discharge measured at the Heyuan hydrological station in the period from 2001 to 2020 are taken as a case study. The results show that (1) the optimal bivariate copula function for annual maximum 1-day rainfall and annual maximum discharge is the Clayton Copula; (2) similarly, the optimal bivariate combined probability function for rainfall-induced landslides is the Gumbel Copula; and (3) the combined hazard thresholds of multiple disaster-causing factors for rainfall-induced flash floods and landslides differ substantially from the thresholds based on single disaster-causing factors. Taking the return period of 100 years as an example, the univariate thresholds of discharge and rainfall are 8530.38 m3/s and 217.82 mm, while the combined thresholds decrease to 5793.10 m3/s and 175.22 mm. Meanwhile, the univariate thresholds of rainfall and landslide probability are 195.02 mm and 0.82, but the combined thresholds decrease to 170.81 mm and 0.78, respectively. In other words, conventional single-factor threshold calculation methods can severely underestimate the actual hazard level, and coupling among multiple factors can induce a significant disaster superposition and amplification effect. This study reveals the risk-coupling mechanism of heavy rainfall hazards and provides technical support for the accurate identification, prediction, and early warning of rainfall-induced flash floods and landslides under climate change.

Urban Science doi: 10.3390/urbansci10090500

Authors: Adnane Labbaci Salwa Belaqziz Hassan Radoine Laila El Ghazouani Asia Lachir

Surface urban heat island (SUHI) behavior in dryland cities can reverse sign when hot, bare peripheral surfaces exceed urban-core temperatures, yet long monthly records across contrasting climates remain scarce. This study reconstructs land surface temperature (LST) and standardized urban-core–periphery thermal contrasts for five Moroccan cities from 1995 to 2024 using Landsat, ERA5-Land, NDVI, and the annual MODIS MCD12Q1 land-cover product. The diagnostic analysis of SUHI and Urban Heat Sink (UHS) occurrence is explicitly separated from the forecasting component: SARIMA, Random Forest, XGBoost, and LSTM models predict monthly LST rather than UHI intensity. Tangier exhibits a persistent positive SUHI (mean: 4.6 °C; UHS frequency: 3.0%), whereas Béni Mellal, Ifrane, Laayoune, and Taza have negative mean contrasts of −1.4, −2.4, −1.0, and −0.7 °C, respectively; Ifrane records the highest UHS frequency (90.5%). No city shows a statistically significant monotonic UHI trend, and Sen’s slopes remain close to zero. Forecasting skill is city-dependent: SARIMA performs best in Ifrane and Tangier (R2 = 0.94 and 0.93), while Random Forest performs best in Taza and Laayoune (R2 = 0.90 and 0.79). Approximate 95% empirical uncertainty half-widths derived from held-out RMSE range from ±3.78 to ±15.48 °C, indicating substantial model- and city-specific uncertainty. The results support the hypothesis that local climate and peripheral land-cover context can outweigh urban fraction as controls on SUHI sign and amplitude. Generalization is limited by fixed reference distances, possible urbanization of the outer ring, clear-sky satellite sampling, the distinction between LST and air temperature, and the 36-month recursive forecasting chain used to display the 2026–2027 outlook.

Urban Science doi: 10.3390/urbansci10090498

Authors: Irma Kveladze

Urban expansion, peri-urban growth, and evolving mobility service systems are reshaping the functional links between urban and rural areas. As these relationships become increasingly complex, conventional urban–rural classifications may underestimate the spatial differences in everyday accessibility, environmental conditions, and demographic exposure. To capture these interrelated dimensions, this study develops a GeoAI-enabled Accessibility–Environment–Equity (AEE) framework to analyse the urban–rural continuum as a multidimensional functional space. Using Odense municipality as a case study, the framework incorporates network accessibility indicators, environmental benefit and pressure proxies, and demographic exposure indicators within a hexagonal tessellation. The indicators are combined into a standardised AEE feature matrix, interpreted through a principal component analysis, and classified using Gaussian mixture modelling with posterior-probability uncertainty mapping. The resulting typology shows a distinct but non-uniform core–periphery gradient: the central areas exhibit high accessibility and population density but lower green space availability and higher environmental pressure proxies, while the peripheral areas are greener but less accessible by non-car modes. The benchmarking against single-domain reference classifications reveals that the functional typology is primarily shaped by accessibility and demographic density structures rather than by greenness alone. This study advances urban–rural continuum (URC) research by demonstrating how GeoAI-enabled workflows can identify functional transition zones and accessibility–environment mismatches, supporting more evidence-based planning for medium-sized European cities and their surrounding urban–rural transition zones.

Urban Science doi: 10.3390/urbansci10090495

Authors: Teqi Dai Shengyao Qin Dingdan Zhang

Urban spatial structure is foundational for planning and management, yet its dynamic and multi-scale nature remains difficult to capture. Travel-flow networks derived from trajectory data provide a useful lens for revealing intra-urban interactions, but conventional community detection methods often overlook the scaling effect of travel distance and intra-day temporal dynamics. To address this limitation, this study proposes a novel framework to delineate urban structure at different scales, which identifies breakpoints in travel distances where interaction patterns shift. The method performs recursive community identification on the traffic flow, which is stratified by equal-distance intervals: it first detects communities using flows within a short-distance threshold, aggregates them into super-nodes, and then considers the short-distance flows and longer-distance flows between these communities and re-detects the communities at this level. When the community structure changes significantly, the flows from the previous distance range are excluded from further analysis, and the previous communities are treated as nodes for the next level, so that hierarchical organization is preserved and scale-specific interactions are isolated. Applying this method to Beijing taxi trajectory data across five time periods, a four-level spatial community structure is revealed: street-scale communities (short-distance flows), district-scale communities (medium-distance flows), urban–rural-scale communities (long-distance flows), and metropolitan-scale communities formed by ultra-long-distance flows. Significant intra-day variations are also identified, with morning-peak and night-time structures differing notably from other periods. The findings offer a multi-scale perspective on urban spatial organization and provide implications for traffic management and urban planning.

Urban Science doi: 10.3390/urbansci10090499

Authors: Luiz Sousa Licinio Portugal

The licensing of trip-generating developments (TGDs) determines how mobility impacts are assessed and which mitigation measures are required, yet procedures remain heterogeneous and largely focused on roadway performance. No instrument was identified to assess their adherence to sustainable urban mobility (SUM) principles. This study proposes a maturity-based protocol for that assessment. It comprises four dimensions, sixteen components, and three maturity levels: N1 conventional, N2 in transition, and N3 SUM-oriented. It derives from an integrative review of the literature and technical and institutional documents. Expert content validation yielded item-level indices of 0.86–1.00 and a scale-level index of 0.94. Inter-rater assessment showed 81.3% exact agreement and an ordinal Krippendorff’s alpha of 0.83. Applied to Rio de Janeiro, it classified five components at N1, ten at N2, and one at N3. Sustainable mobility is reflected in the regulatory vocabulary, in the declared scope of the study, in measures for pedestrians and cyclists, and in the financial instrument, without reaching the metrics that structure the approval decision. By shifting the unit of analysis to the regulatory procedure and presenting a diagnostic profile rather than an aggregate score, the protocol provides a basis designed for replication and comparison across municipal licensing systems.

Urban Science doi: 10.3390/urbansci10090497

Authors: Maciej Piekarski Joanna Dudek

This research addresses an urban problem that has emerged as a result of the increased number of trains on railway line located in a city center. The essence of this problem is the difficulty of crossing individual and public transport lines, on foot and by bicycle, due to the small number of crossings and passages, most of which are single-level. The authors consider the positive aspect of the emergence of a barrier to road transport and aim to solve the problem by ensuring access to the city center for people, not cars. The proposed solution includes a pedestrian and bicycle tunnel and two bus stops located near the tunnel entrances. The tunnel and bus stops are located within the former railway station. This once vibrant area would be revitalized through the creation of a multimodal transfer hub. The research included analysis of traffic study results, observation of a key railway crossing, an urban and functional analysis of the area, and an assessment of the architectural heritage within the former railway station. The design part formulated guidelines for the modernization of the road system, which is necessary to introduce city bus traffic and ensure their priority.

Urban Science doi: 10.3390/urbansci10090496

Authors: Duc Lam Nguyen Ngoc Duc Doan Truc Le Nguyen Van Quy Khuc

The growing pressure of municipal waste generation and its associated environmental consequences has turned household participation into a central challenge for sustainable waste governance and circular-economy transition. This study adopts Cultural Additivity Theory and employs Bayesian Mindsponge Framework (BMF) analytics to examine how interactions between environmental–cultural and governance value bundles shape household willingness to pay (WTP) for improved urban waste management services, using survey data from 352 households in Hai Phong City, Vietnam. The results show that both the perceived importance of Commune Authorities and Women’s Unions are positively associated with WTP. More importantly, environmental perception and behavior further strengthen these governance–WTP associations, indicating that household financial support for improved waste management is greater when governance values interact with stronger environmental–cultural values. In contrast, higher environmental service satisfaction tends to weaken the positive association between governance importance and WTP. These findings suggest that household WTP is better understood as a relational outcome of interacting value bundles rather than as the product of isolated determinants operating independently. This study makes three contributions. First, it extends Cultural Additivity Theory into the field of urban environmental governance by demonstrating how interactions among value bundles shape household environmental decision-making. Second, it advances the waste-management literature by showing that environmental perception and environmental behavior become more influential when embedded within supportive governance and community structures. Third, it provides empirical evidence for developing community-based urban waste-management policies that integrate environmental communication, source-separation initiatives, local governance, and women-led community engagement to strengthen public participation and support sustainable urban waste-management systems.

Urban Science doi: 10.3390/urbansci10090493

Authors: Dirk H. R. Spennemann

In the recent past, digital twins have seen increasing attention in cultural heritage management studies. Digital twins have emerged as dynamic virtual representations of buildings, streetscapes, and urban environments that by integrating sensors, real-time data, and predictive models can support planning, conservation management, and public engagement. As such, digital twins are seen as a panacea by some urban planners, positing that they can function as archival substitutes for heritage streetscapes to be demolished within the context of increasing urban densification pressures. This paper examines this question by first reviewing the development and purpose of heritage conservation areas (historic districts, conservation areas, conservation districts) internationally, highlighting the longstanding tension between heritage conservation and urban renewal. Drawing on examples from Australia and overseas, the discussion evaluates both opportunities and limitations of digital twins for documenting and conserving heritage streetscapes. The paper argues that, depending on the level of detail recorded, digital twins can effectively replicate many ontic dimensions of heritage environments, including physical form, façades, infrastructure, and environmental conditions, while supporting the modelling of development scenarios and the assessment of their impacts. However, digital twins cannot fully capture the ontological dimensions of heritage, such as authenticity, sensory immersion, cultural meaning, atmosphere, and sense of place. Using the Swift Street Heritage Conservation Area in Albury (New South Wales, Australia) as a minor case study, the paper discusses how fine-grained material and craft details can often be lost in digital representation. The paper concludes that while digital twins are valuable tools for documentation and planning, they cannot fully replace the cultural significance embodied in original heritage fabric. In consequence, they cannot be given equivalency with the originals and thus cannot be used as substitutes.

Urban Science doi: 10.3390/urbansci10090494

Authors: Hlengiwe Precious Kunene

The consequences of changing climate conditions and associated extreme weather are increasingly discussed in the global railway transport sector, as infrastructure damage and service disruptions are more widely reported. The Passenger Rail Agency of South Africa (PRASA) is a critical component of the national passenger rail service that provides safe, reliable and affordable rail services to millions of passengers annually. However, the increasing recorded frequencies of extreme weather events in the country means that PRASA’s operations and infrastructure are not exempt from these emerging hazards. This provided an opportunity for the study to assess the spatio-temporal exposure and climate risk of climate-related extreme weather events to PRASA infrastructure and operations. The study drew on the strengths of a mixed-methods approach, integrating quantitative and qualitative techniques. It combined recorded historical extreme-weather event data from the South African Weather Service (SAWS) with expert-based focus group discussions to address the research questions. Findings show an increase in the recorded frequency of extreme weather events over a period of 103 years (1920–2022) in both areas. These hazards indicate exposure that can lead to damage to physical rail infrastructure and to train service disruptions. In both areas, Kendall’s tau indicated significant positive monotonic trends in the frequency of several weather-related hazards over time. Focus group findings identified coastal flooding, flash floods and sea-level rise as the top priority climate-related risks for PRASA along other key infrastructure vulnerabilities. On this basis, the study recommends both rail infrastructure and operational adaptations.

Urban Science doi: 10.3390/urbansci10090492

Authors: Majida Yakhlef

Refugee camps have evolved from temporary shelters into permanent, complex urban systems, yet policy models often fail to address their long-term systemic marginality. To bridge this gap, this study conducts a comparative qualitative analysis of three protracted cases in the Middle East: Shatila (Lebanon), Yarmouk (Syria), and Jabalia (Gaza). Using a directed qualitative content analysis, the study evaluates secondary data, spatial reports, and institutional archives across five core System Pillars: Governance Configurations, Legal Regimes, Humanitarian Mediation, Spatial Violence, and Grassroots Agency. Findings show that conditions of urban exception are sustained by a self-reinforcing nexus of these processes. Furthermore, a dual-process model of refugee agency emerges, distinguishing short-term adaptive survival tactics (e.g., informal DIY utility grids) from constitutive practices of urban citizenship that reconfigure institutional aid protocols. In post-conflict contexts, physical destruction is systematically coupled with state-led property legislation to enforce permanent displacement. We conclude that protracted camps must be recognized as dynamic, co-produced urban systems rather than static zones of exception. Effectively breaking cycles of socio-spatial marginalization requires international actors to transition from short-term emergency assistance to rights-based metabolic planning, legal tenure protection, and formalized institutional co-production frameworks.

Urban Science doi: 10.3390/urbansci10090491

Authors: Sunanda Kapoor Bibhu Kalyan Nayak Vandana Sehgal

The quantitative measurement of TCC at tourist cities involves considerable methodological complexities. Conventional evaluation methods based on fixed numerical criteria are frequently insufficient since tourism systems are characterized by unclear information, gradual shifts, and subjective experiences. To address these methodological constraints, this study develops and implements a hybrid FAHP-weighted Fuzzy Comprehensive Evaluation (FCE) framework to estimate TCC. The framework incorporates four critical indicators, visitor density, waste generation, infrastructure load, visitor perception, reflecting the physical, environmental, infrastructural, and socio-cultural dimensions of tourism development. These indicators are assessed using a structured analytical procedure integrating fuzzification, expert-derived weighting through the fuzzy analytic hierarchy process, fuzzy comprehensive evaluation, and centroid defuzzification. This study presents a hybrid SEM–FAHP–FCE framework, which is a multi-method integrated decision model that combines SEM (structural equation modeling) for visitor perception and behavioral drivers, FAHP (fuzzy analytic hierarchy process) for expert-based indicator weighting and FCE (fuzzy comprehensive evaluation) for final carrying capacity assessment under uncertainty. This combined methodology offers a more adaptive and empirically grounded assessment of TCC by synthesizing quantitative conditions with qualitative stakeholder perceptions within a unified evaluative model. The framework is validated through empirical application to Vrindavan, Uttar Pradesh, one of India’s most visited destinations, across eight study sites and two seasonal conditions (normal and festival-peak). Primary data collection comprises 300 visitor count observation units and field data, i.e., visitor count, waste generation and infrastructure details. The defuzzified FAHP–FCE results for each site (W = 3.94, 3.33, 2.44, 1.95, 3.66, 1.87, 1.86 and 2.71) reveal that major pilgrimage nodes exhibit scores approaching the upper bound of the evaluation scale, indicating that tourism pressure has significantly exceeded carrying capacity during peak periods. This study establishes proof-of-concept for the FAHP–FCE framework as a standardized, replicable instrument for evidence-based TCC governance at tourism cities.

Urban Science doi: 10.3390/urbansci10090489

Authors: Ufuk Fatih Kucukali Pınar Öktem Erkartal Dilek Yasar

Community-scale sustainable built-environment practices are increasingly important for linking urban sustainability policy with everyday spatial transformation, yet the evidence base remains fragmented across nature-based solutions, housing retrofit, settlement upgrading, public-space transformation, digital mapping, circular infrastructure, and governance-oriented planning. This scoping review, reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR), maps and synthesizes peer-reviewed evidence on community-scale sustainable built-environment practices, with publication years from 2015 to 2026 and indexed by the final search date of 13 June 2026. Searches were conducted in Scopus and the Web of Science Core Collection, yielding 3506 records. After duplicate removal, title-and-abstract screening, and full-text eligibility assessment, 130 studies were included for Spatial–Social–Governance (SSG) coding and thematic synthesis. This review identified eight thematic clusters, led by nature-based and green–blue infrastructure practices, followed by housing, retrofit, and settlement upgrading; neighborhood sustainability assessment and planning; public-space transformation and placemaking; digital tools and mapping; circular neighborhood infrastructures; mobility-related practices; and heritage-led regeneration. The largest concentration of evidence was found in nature-based and green–blue infrastructure practices, followed by housing, retrofit, and settlement upgrading; smaller clusters extended the field towards neighborhood assessment, public-space transformation, digital evidence systems, circular infrastructures, mobility, and heritage-led regeneration. As a review-derived synthesis output, the Spatial–Social–Governance Mechanism Framework does not introduce spatial, social, and governance as new analytical dimensions. Instead, it operationalizes these established concerns as a common comparison structure for heterogeneous community-scale built-environment practices, linking spatial intervention, social embedding, and governance enablement. The framework is neither a general theory nor an effectiveness model; its contribution is an integrative and review-specific analytical instrument.

Urban Science doi: 10.3390/urbansci10090490

Authors: María José Delgado-Iniesta Pura Marín-Sanleandro Ángeles Gallegos Francisco Bautista Henry Paul López Bayas Elvira Díaz-Pereira Antonio Sánchez-Navarro

In 2023, Murcia implemented a new sustainable urban Mobility Plan emphasizing pedestrianization, segregated public transportation, and the reduction of private vehicle traffic within the city. Consequently, this study aimed to evaluate heavy metal pollution in urban dust by comparing data collected prior to the plan’s implementation (2016) with that obtained afterward (2025). Systematic sampling of urban dust was conducted at 84 sites during both study periods. The concentrations of elements were quantified employing inductively coupled plasma mass spectrometry. The K-means algorithm was employed to identify data clusters. The analysis revealed a distinct geochemical shift, with the dominant elemental abundance changing from Fe > Zn > Mn > Pb > Cu > Cr in 2016 to Fe > Zn > Mn > Cu > Cr > Pb by 2025. Concentrations of Pb and Mn declined following the implementation of the Mobility Plan, whereas levels of As exhibited an increase between 2016 and 2025. Children are at risk of exposure arising from As, which was identified as the contaminant of greatest concern. The Murcia Mobility Plan, implemented in 2023, had a significant and multifaceted impact. It led to a decrease in traditional metal contaminants and simultaneously highlighted the emergence of new contaminants, such as arsenic (As).

Urban Science doi: 10.3390/urbansci10090488

Authors: Dana Khalid Amro Suheir M. S. Ammar Salam AbuAl-Qumboz

Post-conflict reconstruction under prolonged blockade and governance fragmentation has rarely been examined empirically at the neighborhood scale. This qualitative single-case study investigates housing reconstruction in Al-Qubba, Gaza City, following the near-total destruction of the 2014 conflict. A three-dimensional analytical framework- physical quality, community agency, governance, and structural constraints is applied through the cross-cutting lens of Gaza’s blockade ecology. Data were triangulated across semi-structured interviews (n = 25), GIS spatial analysis, Space Syntax assessment (DepthmapX), and institutional document review. On physical quality, reconstruction met the minimum Build Back Better (BBB) threshold: reinforced-concrete roofing replaced pre-war structures, streets were standardized to 10 m and over 75% were paved, while 94.7% of residents expressed satisfaction; however, Space Syntax analysis revealed that Global Integration recovered only to 1.07 against a pre-war baseline of 1.28, indicating functional recovery without spatial optimisation, and public space provision was entirely unrealised. Regarding community agency, the hybrid owner-driven model produced multi-stage participation in 14/20 households (70%), substantially exceeding agency-driven equivalents, with participation depth positively associated with satisfaction through a perceived legitimacy mechanism; however, neighborhood-scale collective participation was absent. On governance, GRM material delays averaged three to six months; approximately 6/20 households (32%) were undercompensated by donor floor-area caps; and only 8/20 respondents (40%) reported concurrence between official and self-assessed damage valuations. The findings characterize Al-Qubba as demonstrating incremental resilience-building rather than transformative regeneration, and contribute four theoretical constructs: a two-tier BBB for siege contexts; blockade ecology as a BBB modifier; incremental resilience under siege; and configurational BBB assessment. As a single qualitative case study, findings are analytically transferable to comparable constrained reconstruction contexts rather than statistically generalizable.

Urban Science doi: 10.3390/urbansci10080487

Authors: Fatima Zohra Mokeddem Naima Hadj Mohamed Zahia Meghnous Dris Zouaoui R. Harrat Walid Mansour Mohammed Chatbi Aida Achour Nahla Hilal

Rapid urban expansion in arid intermediate cities often produces fragmented urban structures that exacerbate inequalities in public transport accessibility and hinder sustainable mobility. However, the relationships between urban fragmentation, transport accessibility, and travel behavior remain insufficiently explored in pre-Saharan cities. This study investigates these interactions through the case of El Bayadh, Algeria, using an integrated methodology combining urban morphological analysis, Geographic Information Systems (GIS), a household survey of 577 households, traffic counts, institutional interviews, and spatial equality assessment based on the Gini coefficient. Public transport accessibility was evaluated using a 300 m walking threshold, complemented by sensitivity analyses at 400 m and 500 m. The results indicate that approximately 65% of the population lives within 300 m of a bus stop, although coverage is strongly concentrated in central districts. A Gini coefficient of 0.41, provided by the El Bayadh Directorate of Transport and computed across 20 urban zones, indicates moderate-to-high spatial inequalities in accessibility that persist despite increasing the service threshold, suggesting that these disparities are more closely associated with urban fragmentation than with the specific walking-distance threshold used to define service coverage. The transport network comprises 11 bus routes, approximately 160 bus stops, and 90 km of routes; however, limited service quality and uneven spatial distribution contribute to a high dependence on private transport, with 45% of trips made by private car, 35% by taxi, and only 20% by bus. These findings are consistent with accessibility inequalities arising from the mismatch between fragmented urban morphology, centralized urban functions, and the configuration of the public transport network. The proposed framework provides transferable insights for planning more equitable and sustainable mobility systems in rapidly urbanizing arid intermediate cities.

Urban Science doi: 10.3390/urbansci10080486

Authors: Ermes Lo Piccolo Barbara Mariotti Francesco Ferrini

The global population is becoming increasingly urban, with approximately 68% of people projected to live in urban areas by 2050 [...]

Urban Science doi: 10.3390/urbansci10080485

Authors: Zamokuhle Mbandlwa Maliga (Mal) Reddy

This study examines the complex dynamics of water scarcity and infrastructure challenges in eThekwini Metropolitan Municipality, KwaZulu-Natal, South Africa. Despite its coastal location, the municipality faces persistent water shortages driven by rapid population growth, urbanization, climate change risks, aging and deteriorating infrastructure, and service delivery constraints. Communities including KwaXimba, Phoenix, Inanda, and Tongaat experience inconsistent access to clean water. The study aimed to identify root causes of scarcity, assess the effectiveness of existing water infrastructure, and propose sustainable, community-informed strategies to improve water resilience and equitable access. A qualitative research design was adopted to capture lived experiences and perceptions of water access across seven wards (1, 3, 52, 54, 56, 57, and 61), representing approximately 357,492 residents. Focus group discussions involved five randomly selected participants per ward, identified through councilor databases. Structured discussions were recorded for accuracy. Data were transcribed and analyzed using NVivo through systematic coding, thematic analysis, and organization of data into structured project folders aligned with research objectives. The analysis revealed recurring themes related to infrastructure decay, climate vulnerability, rapid urban expansion, and service delivery inefficiencies, highlighting significant barriers to reliable water access and community well-being. Findings provide evidence-based insights to guide policymakers, planners, and water authorities in strengthening infrastructure planning, climate resilience, and sustainable water governance.

Urban Science doi: 10.3390/urbansci10080484

Authors: Karima Kourtit Peter Nijkamp Antonia Gravagnuolo Tomaz Ponce Dentinho

Tourism is a complex economic activity all over the world shaped by distinct local resources: culture, nature, industrial heritage, urban ambiance, place-based uniqueness, and geographical accessibility. The simultaneous governance and management of economic growth motives, preservation of the cultural heritage base, and respect for nature and ecological quality calls for an evidence-based and multi-faceted policy analysis that seeks to achieve sustainable development among conflicting policy objectives in tourist areas. The present paper seeks to explore the feasibility of a sustainable balance for various heterogeneous cultural heritage areas in Europe (‘urban pilot regions’), with particular attention to sustainable local development characterized by circular economic objectives and an ecological balance strategy based on the principle of stakeholders’ co-creation. The paper addresses the knowledge gap between generic policy aims and site-specific views of actors or visitors. To that end, an extensive survey experiment was administered in the urban regions concerned, in which a wide range of relevant management issues/questions related to environmental preferences and perceptions were posed to stakeholders and visitors. The data were analyzed by means of a novel respondent-oriented multivariate statistical tool, viz. Generalized Q-Analysis, which is suitable for handling big databases with many respondents. The paper shows that the application of Generalized Q-Analysis to common survey data enriches the results from the application of a conventional Q-Analysis. Furthermore, the study also highlights that, based on the views expressed by the surveyed visitors, the tourist areas concerned are quite different from each other in attracting specific classes of visitors. Therefore, functional specialization in the tourist sector seems to be an important anchor point for effective governance of urban tourism, not only in Europe, but also elsewhere in the world.

Urban Science doi: 10.3390/urbansci10080483

Authors: Amey Shirish Shrotri Karippur Nanda Kumar

India is the most populous country in the world, with a rising urban population and witnessing a surge in noncommunicable diseases such as cancer that impose significant pressure on healthcare professionals, hospitals, and city planners. Over the last decade, India has pursued a vision to transform urban areas into smart cities and roll out digital infrastructure. Rapid urbanization coupled with an ageing population has accelerated demand for precision cancer care (PCC) solutions using advanced technologies such as digital twins (DT), leveraging the developing digital infrastructure in urban India. The fast evolution of e-health technologies and digital infrastructure outstrips healthcare professional readiness, creating challenges for DT adoption for PCC. Past studies on DT adoption primarily focused on organizational adoption and technical implementation challenges. This study addresses this research gap by leveraging the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to investigate the factors that influence the adoption intention of DT for PCC in urban India. The article reports actionable insights and implications for researchers, healthcare professionals, top management of hospitals, smart city planners, government agencies, and urban policymakers. The study will assist stakeholders such as cancer care organizations, technology service providers, and city planners in planning, designing, and implementing DT for PCC.

Urban Science doi: 10.3390/urbansci10080482

Authors: Silvestar Grabušić Danijela Barić Komil Turaev

Trespassing on railway tracks represents the main cause of accidents in railway transport, often resulting in severe injuries and fatalities. Understanding railway trespassing requires integration of multiple data sources, as accident data alone do not capture its spatial and behavioural characteristics. This study identifies key parameters (variables) for developing a QGIS-based trespassing database. It represents the first step toward creating a comprehensive risk assessment tool for the railway network’s susceptibility to trespassing and the potential risk of trespass-related accidents. The methodology integrates secondary data sources, including accident records, railway infrastructure data, and demographic and socioeconomic data, with primary data collected at trespassing locations (GPS coordinates, behavioural observations, patterns, and environmental characteristics). A key challenge was integrating data from multiple sources into a unified database suitable for GIS spatial analysis. The results include mapping trespassing locations by kilometre position and GPS coordinates, as well as creating a structured multimodal database containing detailed information. The developed database enables spatial analysis, supports the identification of trespassing hotspots and provides a foundation for trespassing prevention.

Urban Science doi: 10.3390/urbansci10080481

Authors: Yongzhang Liu Na Luo Jinyu Lan

Industrial legacy cities are trapped in carbon lock-in—a self-reinforcing condition where fossil-fuel infrastructure, industrial structures, and institutional inertia collectively resist urban energy transition. Yet whether and how industrial upgrading policies (IUP) can effectively disrupt this lock-in remains unclear. Using panel data from 148 Chinese legacy cities over 2012–2022, we employ a staggered difference-in-differences model combined with policy-text quantification to evaluate the effects of IUP. Results show that IUP significantly raises urban energy transition by 2.52 percentage points, with technology-enabling instruments delivering the strongest leverage among the three policy tool categories. Mechanism analysis uncovers a co-evolutionary mismatch: green technology innovation mediates 42.21% of the total effect, while the mediating pathway through energy consumption structure remains statistically insignificant—evidence that production-side innovation and energy-side infrastructure exhibit systematically divergent adjustment elasticities in response to industrial upgrading policy. Policy effects also differ across city types, with stronger responses in old industrial base, regenerative, and single-type cities. These findings advance carbon lock-in theory by identifying co-evolutionary mismatch as a distinct source of structural friction in urban industrial transitions and provide actionable pathways for aligning urban industrial restructuring with decarbonization goals.

Urban Science doi: 10.3390/urbansci10080480

Authors: Zofia Czaplicka Aleksandra Krzemień Anna Czaplicka Magdalena Jagiełło-Kowalczyk

The Christmas period reshapes urban cultural experience by temporarily suspending everyday routines and placing collective celebration at the centre of public space. During this time, festive illuminations transform cities, intensifying the symbolic role of light and reinforcing seasonal rituals of exceptionality. In many European cities, large-scale decorative lighting is used not only for aesthetic enhancement but also to create distinctive urban atmospheres. This study examines the effects of seasonal festive lighting on light pollution and perceptions of urban space, using Funchal (Madeira, Portugal) as a case study. Combining in situ photometric measurements, satellite-derived night-time data, and a questionnaire-based perception survey, this mixed-methods study compares periods when festive lighting was active and inactive. The results indicate that Christmas lighting was associated with higher levels of artificial illumination, shifts in the spatial distribution of artificial light at night (ALAN), and changes in night-sky brightness. These findings suggest that festive lighting shapes both the visual character of urban space and the seasonal dynamics of light pollution.

Urban Science doi: 10.3390/urbansci10080479

Authors: Manuel Rivera Mateos

The Historic Centre of Córdoba (Spain), designated a Site of Cultural Interest (BIC) and partially recognised as a ‘World Heritage Site’ by UNESCO, is one of the largest in Europe and, in recent decades, has undergone profound functional, economic and social transformations, which have been accelerated by growing tourist activity. These processes have not yet been analysed systematically, despite the fact that the study of urban processes such as touristification and their implications for certain urban dynamics of gentrification is a highly topical issue. This study aims to determine the extent to which the Historic Centre of Córdoba is undergoing a significant process of touristification and its impact on depopulation, gentrification and other functional and land-use transformations. To this end, a series of demographic, socio-economic, tourism-related and property market indicators have been collected and analysed. The results indicate a recent, intense process of touristification that has exacerbated the critical situation of depopulation and residential abandonment, although no significant process of socio-demographic gentrification has been detected. It is concluded that tourism is neither the sole nor even the main cause of this trend of demographic decline and functional and urban changes; rather, there are multiple historical, socio-economic, urban planning and demographic factors that explain them. This study lays the groundwork for a broader investigation of this urban area, which is of such great significance to the city in terms of heritage, history and identity.

Urban Science doi: 10.3390/urbansci10080477

Authors: Néstor Santillán-Soto David E. Flores-Jiménez Alejandro A. Lambert-Arista Jose Ernesto López-Velázquez Sara Ojeda-Benítez Nicolás Velázquez-Limón

This study investigates the influence of near-surface air temperature on the performance of internal combustion engines during mobile transects conducted in Mexicali, Baja California, Mexico, one of the hottest cities in North America. Field measurements were carried out along a 15 km urban transect on representative days in April, August, and February. Air temperature and relative humidity were recorded simultaneously at two engine air intake heights (0.66 m and 2.5 m), complemented by surface temperature data obtained from both in situ measurements and Landsat 8 thermal imagery. The results indicate that near-surface air temperature exhibits considerable spatial and temporal variability and is closely associated with land surface temperature (LST) patterns derived from satellite observations. The correction factor (Cf), used to quantify the combined effects of air temperature and atmospheric pressure on engine performance, showed that extremely high temperatures (approaching 50 °C) may reduce engine performance by up to 3.35% relative to standard test conditions. Conversely, cooler winter conditions may improve engine performance by approximately 4.6%. These results suggest that vehicle operation under extremely hot climatic conditions may deviate from the standardized assumptions adopted by the Intergovernmental Panel on Climate Change (IPCC) for emission factor estimation. This study contributes to a better understanding of the effects of extreme urban heat on vehicle performance and demonstrates that localized thermal conditions may influence the assumptions commonly used in vehicle emission assessments. The findings provide valuable information for improving greenhouse gas emission inventories and support evidence-based climate adaptation and urban planning strategies in arid cities.

Urban Science doi: 10.3390/urbansci10080478

Authors: Eduardo Medeiros Filipe Ferreira

This article investigates the role of European Union (EU) Cohesion Policy (2021–2027) integrated urban development (IUD) strategies in Portugal in supporting the reduction in social segregation and vulnerability. Mostly based on a literature review and field research, the research concludes that the analysed IUD devotes a minor financial support package to social segregation and vulnerability. Even so, the IUD strategies have contributed to supporting the active inclusion of vulnerable social groups, improving access to employment, skills, and qualifications for young and vulnerable social groups, reinforcing equal access to quality services and social protection, and promoting the active inclusion of socially vulnerable groups and social housing.

Urban Science doi: 10.3390/urbansci10080476

Authors: Alessandra Ricciardelli Alessandro Cariello Paola Amoruso Felicia Di Liddo

Urban regeneration has become a key strategy to address urban decline, infrastructure aging and socio-economic challenges, aiming to enhance quality of life and stimulate local development. Beyond physical renewal, it involves social, cultural and economic dimensions that contribute to the revitalization of communities. Recent literature frames regeneration as an adaptive and multifaceted process, drawing on concepts such as change management, dynamic capabilities and sensemaking to interpret urban transformation as a form of institutional learning. This study adopts a qualitative case study approach focused on the Libertà district in Bari (Italy), using document analysis, field observation, and stakeholder mapping to investigate both tangible and intangible outcomes of regeneration policies. Particular attention is devoted to understanding how socio-institutional and spatial transformations are translated into economic outcomes, using residential property values as an exploratory indicator of economic change. In this regard, variations in residential property values are considered as an exploratory indicator of economic dynamics associated with regeneration, while acknowledging that property price increases do not necessarily correspond to benefits for all community members and may also reflect issues related to affordability and social displacement. The findings suggest that regeneration should be understood as a coordinated and collaborative process involving multiple stakeholders and institutional actors. The analysis highlights the relevance of cultural initiatives, stakeholder interactions and changes in the physical environment as key elements of the transformation process. Furthermore, the study discusses the extent to which changes in the local real estate market may be associated with broader regeneration dynamics, recognizing the limitations of establishing direct causal relationships. Overall, the research proposes an original perspective on urban regeneration as a learning-based and organizational process in which social, institutional, and spatial transformations interact with economic change in complex and context-dependent ways.

Urban Science doi: 10.3390/urbansci10080475

Authors: Qiaozhi Zhao Ding Jia

Cities, being elementary concentrations of socio-economic activities and resource-environmental pressures, confront significant challenges in promoting new quality productive force (NQPF) development because technology, resource, and information conditions may be spatially associated across cities. Although the nexus among cities has gained widespread recognition in China’s high-quality development such as in innovations and low-carbon transformation, a critical gap exists in quantitatively assessing how model-estimated inter-city spatial correlations relate to high-quality development within an integrated framework. To bridge this gap, this study constructs an urban social correlation network (SCN) analysis framework, integrates spatial correlation methods to overcome the limitations of traditional heterogeneity assessment, and applies it to 283 Chinese cities from 2010 to 2023 to measure network characteristics and structural resilience related to NQPF. The results show that the network density rose from 0.0608 in 2010 to 0.1577 in 2023. By 2023, the SCN featured higher connectivity and reciprocity, comparatively high but lower efficiency, low hierarchy, and no obvious core–periphery structure. The 283 cities were divided into four blocks, exhibiting denser intra-regional than inter-regional links, and strengthened inter-regional interactions over time. The displayed node-removal trajectories declined faster under centrality-ordered removal than under one reported random-removal sequence. The network was more vulnerable to intentional attacks than to random attacks. Motif analysis indicates that M1 and M2 dominated and contributed to low network density, while the shift from open structural holes toward a mix of open and closed structures was associated with network evolution. These findings indicate that cultivating key node cities and improving inter-city coordination mechanisms to enhance network resilience are critical pathways for advancing NQPF development with Chinese characteristics, providing quantitative evidence for targeted inter-city coordination policymaking.

Urban Science doi: 10.3390/urbansci10080474

Authors: Mauricio Salas-Salinas Francisco L. Quispe-Huacca Jessica L. Curo-Mamani Maria C. Soto-Rojas Alexander A. Torres-Auccapuri Estéfany M. Choque-Condori Mayrin R. Hañari-Nina Arlette M. Estrada-Lupaca Franco E. Linghán-Marca Lizeth A. M. Ari-Gutierrez Emmir O. Chavez-Cayo Giovanni Aragón-Alvarado Ruth M. Mamani-Contreras

Urban expansion generates habitat fragmentation, light pollution, and vegetation loss, driving biodiversity decline globally. Insectivorous bats are particularly suited to track these changes: their taxonomic and functional diversity, combined with their differential sensitivity to landscape configuration and roost availability, makes them reliable bioindicators of urbanization impacts. This study characterized bat acoustic diversity and community composition along an urban–rural gradient in Tacna, Peru, using passive acoustic monitoring. Twenty-three stations equipped with autonomous ultrasonic recorders were established between December 2024 and April 2025. Sonotype identification was validated through linear discriminant analysis (DFA), achieving 94.47% accuracy by Leave-One-Out Cross-Validation (LOOCV). Nine sonotypes were identified, seven Molossidae and two Vespertilionidae; Myotis atacamensis showed the highest detection frequency across all districts. Diversity indices were highest in the peri-urban zone of Pocollay (S = 8; H′ = 1.664) and lowest in Gregorio Albarracín (S = 4; H′ = 0.964). The high dissimilarity between Pachía and the urban core of Tacna (BC = 0.817) points to marked compositional differences linked to urbanization intensity. Records of Nyctinomops laticaudatus and N. macrotis constitute the first documentation for the urban area of Tacna. These results suggest urban and peri-urban sectors may function as ecological oases for bat sonotypes within a hyperarid matrix, providing a baseline for evaluating the role of green spaces, landscape connectivity, and artificial lighting in arid cities.

Urban Science doi: 10.3390/urbansci10080473

Authors: Atef Ayed Ghumaid Faisal Mnawer AlMayouf Ayed Mohammad Taran Khawla Abed Almohdi Al Maayah Hamzeh Mohamed Bani Khaled Bashar Ali Khawaldah Eman Mohammad Khamis Ghazi Lafe Alserhan

The extensive use of high-resolution digital elevation data, along with continuous improvements in computing power and geographic information system (GIS) tools. Has driven the development of spatial data processing, management, and spatial interpolation methods. This study aims to construct a high-quality spatial distribution map of thermal comfort in densely populated areas of northwestern Jordan using climate data collected from six meteorological stations between 1991 and 2024, based on the indoor temperature index (IAT). To analyze the spatial variability of climate elements, a digital elevation model (DEM) with a spatial resolution of 30 m was used and resampled to a 0.5-km grid. Spatial interpolation employed inverse distance weighting (IDW), with each grid cell using data from the three nearest meteorological stations. The results showed that areas with higher temperatures inside the villas were clearly concentrated in the summer, especially in the lowlands near the Jordan Valley. Indicating that these areas are more susceptible to thermal stress. The model results also show that it performs well in predicting thermal comfort, with a coefficient of determination (R2) between 0.95 and 0.98 and mean squared error (MSE) between 0.35 and 0.50. which reflects the ability of these models to represent the relationship between climate variables and predict thermal comfort levels with a high degree of accuracy. The results indicate significant spatiotemporal differences in thermal comfort within the study area, with longer durations of heat stress in summer. This highlights the importance of combining geospatial methods with numerical simulations in studying the impacts of climate change and supporting urban planning and climate adaptation strategies.

Urban Science doi: 10.3390/urbansci10080472

Authors: Daniel D. Otero Meza Alexis Sagastume Gutiérrez Juan J. Cabello Eras

Whether economic growth decouples from municipal solid waste (MSW) generation in upper–middle-income economies remains contested. We test the Waste Kuznets Curve and a disposal-to-recovery substitution effect using a 13-year panel of 1101 Colombian municipalities, combining step-wise fixed-effects models with a non-parametric generalized additive model (GAM), a family of spatial specifications, and a selection-aware recovery model. We find no evidence of income-driven decoupling in landfilling. Once the urban density and demographic structure are controlled, the income terms lose significance, the non-parametric estimate is predominantly monotonic, and density emerges as the main structural driver. Material recovery grows faster than disposal with income (relative substitution), but this signal is concentrated where recovery is measured—only 27% of municipalities report it, and coverage falls from every metropolitan municipality to one in five in the rural periphery, and the income terms are stable across every spatial representation—so that once selection is corrected the recovery elasticity falls from about 5.9 to a non-significant 1.3. Rather than spontaneous decoupling, Colombia exhibits persistent coupling alongside an institutionally engineered, spatially unequal recovery capacity. Achieving SDG 12 therefore requires stratified policies that mandate consumption reduction in mature urban economies while subsidizing shared circular infrastructure for historically neglected rural jurisdictions.

Urban Science doi: 10.3390/urbansci10080471

Authors: Hao Geng Fang Liu Zhitao Zhong Yusong Zhu Jingyi Zhang

The worsening jobs–housing imbalance in high-density urban areas has become increasingly prominent. However, existing studies predominantly focus on the city and regional scales, with limited attention to small-scale spatial units, failing to provide empirical evidence for refined regulation of transport and land use. As a typical compact development mode at the small scale, Transit-Oriented Development (TOD) offers an ideal spatial unit for examining micro-level jobs–housing relationships. However, its influence on jobs–housing balance remains unclear. This study takes 72 built subway station areas in Shenzhen’s highest-density built-up area as the research object. Employing quadratic polynomial regression and XGBoost-SHAP methods, it reveals the effects of transportation supply and land use on the employment–residential ratio, as well as threshold effects and indicator synergies. The main findings are as follows: (1) Transportation supply (Node), land use (Place), and TOD degree (TODness) all exhibit U-shaped effects on the employment–residential ratio, with inflection points at Node = 0.330, Place = 0.412, and TODness = 0.776, identifying the critical transition from balance to employment polarization. (2) Number of subway directions is the most critical indicator, together with betweenness centrality, floor area ratio, population size, and land use entropy, each exhibiting notable threshold effects. (3) A significant interaction effect exists between betweenness centrality and land use entropy, suggesting that traffic network connectivity and land use evenness can jointly regulate the employment–residential ratio in both directions. This study provides a quantitative basis for phased regulation of jobs–housing relationships in high-density TOD station areas, with findings transferable to other high-density cities.

Urban Science doi: 10.3390/urbansci10080470

Authors: Ivana Marjanović Sandra Milanović Zbiljić Milan Marković

European urban policy increasingly requires city benchmarks that are people-centred, multidimensional and methodologically defensible, yet perception-based environmental evidence is rarely aggregated without arbitrary weighting. Accordingly, this paper develops and justifies a synthetic index of perceived urban environmental performance (UEP) for European cities. Specifically, using the environmental module of the 2023 Eurostat Urban Audit Perception Survey (UAPS) for 83 Functional Urban Areas (FUAs), four satisfaction indicators (air quality, noise, cleanliness and green spaces) are aggregated with a benefit-of-the-doubt (BoD) composite indicator that assigns each city endogenous, self-favouring weights. Standard, weight-restricted and cross-efficiency variants are estimated, benchmarked against an equal-weight comparator, and embedded in an exploratory spatial data analysis. The results demonstrate that nine cities form the efficient frontier, led by Oulu, Luxembourg and Zurich, while Skopje, Naples and Athens anchor the lower tail. Additionally, a robust North–South gradient emerges, and green space satisfaction is the dominant structural driver of composite scores, partially compensating weak air quality in many cities. The study addresses perception-based BoD benchmarking—uncovering dimension-specific environmental governance deficits masked by national indicators—and complements objective environmental monitoring for European Union (EU) cohesion and climate-neutrality policy.

Urban Science doi: 10.3390/urbansci10080469

Authors: Dimitrios Kalfas Stavros Kalogiannidis Fotios Chatzitheodoridis Athanasios Papavasileiou

Transportation infrastructure plays a fundamental role in shaping sustainable urban and regional development by improving accessibility, strengthening territorial cohesion, and supporting long-term economic resilience. While previous studies have primarily examined this relationship through macroeconomic indicators and secondary datasets, limited attention has been given to the perceptions of transportation professionals directly involved in infrastructure planning, implementation, and management. Addressing this gap, the present study investigates how transportation professionals in Greece perceive the contribution of transport infrastructure to sustainable regional development within the European policy context. A quantitative, cross-sectional design was employed, administering a structured questionnaire to 384 transportation professionals in October–November 2025. The study examined four interrelated dimensions: socio-economic contribution, environmental sustainability, infrastructure resilience, and long-term development. Multiple regression analysis showed that all four dimensions are significantly and positively associated with perceived regional development, with socio-economic contribution (β* = 0.359) and long-term development (β* = 0.304) showing the largest coefficients (R2 = 0.597, p < 0.001). The study contributes practitioner-grounded evidence from the Greek context, with implications for the European Green Deal, TEN-T, and EU Cohesion Policy.

Urban Science doi: 10.3390/urbansci10080468

Authors: Younsung Kim Colin Chadduck

Urban climate risks, particularly extreme heat and flooding, increasingly threaten public infrastructure in rapidly urbanizing regions. Public schools represent critical community assets, yet their spatial planning often overlooks the role of natural capital in mitigating environmental risks. This study examines the intersection of natural capital and urban design through a case study of public schools in the Mount Vernon District of Fairfax County, Virginia. Using cartographic modeling and spatial analysis, the study assesses school-site exposure to urban heat island effects and localized flood risks by integrating geospatial data on land cover, surface temperature, and hydrological conditions. Results indicate that all analyzed school sites exhibit notable vulnerability to both heat exposure and flooding. The findings highlight the importance of incorporating natural capital—such as expanded tree canopy, green infrastructure, and permeable surfaces—into school site planning to enhance climate resilience and environmental quality.

Urban Science doi: 10.3390/urbansci10080467

Authors: Troy Daniel Glover

Cities increasingly invest in social infrastructure—parks, plazas, libraries, and other shared environments—to foster connection and wellbeing. Yet proximity does not reliably translate into meaningful social interaction, thereby revealing a persistent gap in understanding how connection emerges in urban contexts. This paper advances a relational model of urban social wellbeing that shifts analytical focus from spatial provision to interactional process. Drawing on an integrative conceptual synthesis of urban studies, micro-sociology, and social psychology, the model specifies how environmental conditions shape patterns of engagement over time. Urban social life unfolds as a staged sequence of interactional dynamics that progress from co-presence and recognition through civil inattention, triangulation, acknowledgment, interaction, and repetition. Across these stages, perceived social risk operates as a probabilistic filter that shapes transition likelihoods and explains why interaction often stalls. The paper further introduces social fitness as a contextual and relational capacity that develops through repeated interaction. By distinguishing between relational capacity and relational outcomes, the model explains how social wellbeing emerges through relational layering, as individuals accumulate a portfolio of strong, weak, and invisible ties that support belonging and integration. Conceptualizing urban social life as a dynamic system, the model offers a framework for empirical investigation and positions urban design as the shaping of interactional conditions.

Urban Science doi: 10.3390/urbansci10080466

Authors: Luka Hamel-Serenity

Stresses of climate change, urbanization, and segregation make the City of Norfolk in Virginia’s Tidewater region a fitting context for qualitative research into coastal resilience, urban nature, and residents’ perceptions of the environment. Dissertation research into sea level rise and urban development provided a rich environment for developing a practical multi-method system for community-engaged investigations of flooding effects, gentrification, and the loss of urban nature. Multi-method research illuminates social, racial, and economic dynamics in Norfolk residents through participant observation, archival research, semi-structured interviews, and walking interviews. The data generated by archival content analysis and semi-structured interviews can offer insights into citizens’ roles and experiences regarding climate change, urban development and redevelopment, and distressed nature in the city. Innovative use of participant observation and the walking interview can engage with questions of respondents’ personal beliefs about nature and the city, highlighting new possible applications of these methods. This research adds to the literature on the effects of climate change and displacement in Norfolk’s planning policies. It supersedes discussions of the mechanics of climate change to assess a range of residents’ perceptions on their own terms. The article provides a clear framework for engaging with residents around issues on climate, urbanization, and environmental stress. It therefore offers a methodological contribution to the field of qualitative research in coastal climate change science and the human experience of the dynamic, modern city. The article’s findings and methods may not be applicable in rural areas or in areas which are not facing acute climate change.

Urban Science doi: 10.3390/urbansci10080465

Authors: Carmen Díaz-López Francisco Conejo-Arrabal Dariel López-López Konstantin Verichev

Although conventionally quantified as an urban–rural thermal anomaly, urban heat islands are systematic expressions of development choices that shape unequal exposures and health risks across cities. This article develops an integrated urban development-health framework explaining how imperviousness, vegetation deficit, landscape configuration, urban morphology, thermally absorptive materials and nocturnal heat retention connect heat exposure with physical disease, mental well-being and climate-responsive planning. A critical integrative review reported using PRISMA 2020 and PRISMA-ScR principles, organised evidence from urban climate, public health, environmental epidemiology and planning. The synthesis covers the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Local Climate Zones (LCZs), sky-view factor (SVF), height-to-width ratio (H/W), land-surface temperature (LST), Universal Thermal Climate Index (UTCI), Physiological Equivalent Temperature (PET), wet-bulb globe temperature (WBGT) and nocturnal minimum temperature, together with cardiovascular, respiratory, psychiatric, sleep, mortality and well-being outcomes. Six recurrent amplification pathways were identified: imperviousness and low canopy cover; nocturnal heat retention; social vulnerability; blue-green and cool infrastructure; heat–pollution–humidity interaction; and sleep/mental-health disruption. The Urban Heat-Health Development Index (UHHDI) and Urban Heat-Health Amplification Pattern (UHHAP) are proposed as transparent, review-derived tools for urban diagnosis and policy prioritisation. A Spanish/Mediterranean climatic-zone transition analysis illustrates how future climatic severity can be translated into planning-relevant exposure potential. The findings support a shift from simply describing urban heat to diagnosing development-driven heat-health risk, with implications for urban regeneration, thermal justice, public-health adaptation and healthy-city governance.

Urban Science doi: 10.3390/urbansci10080464

Authors: Hiroko Oe Yasuyuki Yamaoka Max Weeks Sitsada Sartamorn

This study examines how spatial design, particularly lightscape interventions, operates as a behavioral nudge associated with collaborative participation intention in urban environments. Drawing on nudge theory, place attachment, and cultural heritage literature, we analyze data from a questionnaire survey of 720 urban residents across major metropolitan regions in Japan using structural equation modeling (SEM). The results indicate that urban development and cultural heritage assets are positively associated with lightscape interventions, which in turn show a strong positive relationship with collaborative participation intention. While urban development exhibits both direct and indirect relationships with participation intention, the influence of cultural heritage assets operates primarily through lightscape interventions as a mediating mechanism. These findings suggest that cultural heritage alone does not automatically stimulate civic participation; rather, its social value is activated when heritage resources are translated into meaningful spatial and visual experiences. Lightscape interventions thus serve as an effective non-coercive mechanism linking spatial and cultural resources to civic engagement intentions. This research offers valuable insights for urban planners and policymakers seeking design-based, non-coercive strategies to enhance citizens’ place attachment and willingness to contribute to community activities.

Urban Science doi: 10.3390/urbansci10080463

Authors: María Belén Vázquez-Brage Raimundo Otero-Enríquez

This study addresses the need to establish precise variables to assess subjective urban vulnerability, moving beyond the strictly one-dimensional or perceptual–environmental measurements regularly applied in the study of this territorial reality. Following an initial theoretical proposal, a thematic content analysis of semi-structured interviews was conducted with stakeholders who carry out their professional activity in vulnerable neighborhoods. The diagnostic questionnaire was evaluated through a three-round Delphi process by a multidisciplinary panel of experts from the Spanish university system. The results definitively validated 32 indicators, distributed across three dimensions of subjective urban vulnerability: physical space of the neighborhood (16), social identity (8), and social cohesion (8). In conclusion, this framework provides researchers in the field of territorial science and public managers with a validated, precise instrument for designing interventions tailored to the psychosocial complexity of vulnerable neighborhoods, in the Spanish and European context, improving the understanding and management of these spaces.

Urban Science doi: 10.3390/urbansci10080462

Authors: Rodrigo Sant’Ana Nogueira Letícia Peret Antunes Hardt Patrícia Costa Pellizzaro Carlos Hardt

Criminality represents one of the major challenges faced by Brazilian cities, particularly due to the limited state capacity to control violence. To provide support for addressing this issue, the research focuses on systematizing responses to the investigative question regarding the identifiable foundations for sharing urbanistic-criminal solutions within the framework of the urban agenda. With the aim of analyzing this reality through a case study in Itumbiara, Goiás, Brazil, the assessment relied on field surveys and relational analysis of criminal, landscape, and institutional data. Considering three temporal intervals—before, parallel, and after the coronavirus disease 2019 (COVID-19) pandemic—to recognize its influence on the phenomenon under review, the results on the distribution of thefts and robberies along a road sample show a decline in crime even after the official end of the health crisis. Socio-behavioral and socio-political parameters scored lower than socio-morphological ones but overall were classified as medium-low quality. The formulated guidelines combine analytical variables and criminological theories to support public policies for integrated management of safe scenarios, reinforcing the hypothesis that such interactions enable principles for coordinated measures in planning and security in urbanized areas.

Urban Science doi: 10.3390/urbansci10080461

Authors: Anna Szijártó Máté Prohászka Rita Nemes

The construction of adequate infrastructure in low-resource regions is frequently constrained by limited technical facilities, inadequate supply chains, and the absence of standardized quality control. This study presents a case study of the reinforced concrete foundation system of a multifunctional sports hall constructed in Cacine, Guinea-Bissau, where concrete production was carried out under severe logistical and technological constraints. Following construction, laboratory investigations were performed to evaluate the transported cement sample, locally available aggregates, and concrete specimens collected on site. Cement characterization included particle-size distribution, thermal analysis, and compressive strength testing, while the concrete was assessed through compressive strength and water absorption measurements. The aggregate grading complied with the relevant technical requirements and fell within the recommended grading envelope; however, the cement exhibited lower mechanical performance than expected from its declared class, although the non-standard specimen geometry does not permit formal conformity assessment. The concrete reached an average 28-day compressive strength of 12.9 MPa and exhibited relatively high water absorption, reflecting the combined influence of volumetric batching, high water demand, limited mixing efficiency, and the absence of chemical admixtures. Scenario analyses based on the Bolomey relationship indicated that improved control of the effective water-to-cement ratio could substantially enhance concrete performance. Although the study is limited by retrospective testing and a small number of specimens, it provides practical insight into the adaptation of concrete technology to resource-constrained environments and identifies key technological priorities for future infrastructure projects in Guinea-Bissau and similar regions.

Urban Science doi: 10.3390/urbansci10080460

Authors: José-Miguel Giner-Pérez Alvaro de-Juanes-Rodríguez

Digital transformation is portrayed both as a lever of territorial convergence and as a driver of polarisation between urban cores and peripheries, yet its effect on regional economic resilience has rarely been measured systematically. This study transposes the Economic Resilience Index framework from the national to the regional scale, building a Regional Resilience Index (R-ERI) for 236 NUTS2 regions of the EU-27 from Eurostat indicators, anchored in the capacities of absorption, recovery, and adaptation and measuring resilience as a capacity rather than as a realised shock trajectory. Two complementary models are estimated: a spatial Durbin panel with two-way fixed effects (2018–2023), spanning the COVID-19 pandemic and 2022 energy shocks, and an exploratory cross-sectional difference model exploiting regional artificial intelligence (AI) adoption data disaggregated by NACE branch (2023–2025). The results show that resilience is strongly spatially autocorrelated (Moran’s I between 0.66 and 0.74; p = 0.001); that digital connectivity generates a positive indirect effect on neighbouring regions despite a negative own-region effect; and that the synergy hypothesis—that digitalisation yields more resilience when combined with traditional sectors—does not hold robustly, the interaction being null in the panel and only marginally positive in the AI layer (p = 0.10). We conclude that digital connectivity is not, on its own, an automatic convergence mechanism, and that cohesion policy should account for each region’s sectoral structure and peripheral position.

Urban Science doi: 10.3390/urbansci10080459

Authors: Shishir Mathur

This study provides evidence on the impact of a heavy rail-based suburban metro station in Fremont, California, on house prices using geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR). The dataset comprises sale price, sale date, and property and locational characteristics for single-family houses sold during the January 2000–April 2018 period within two miles of the Warm Springs Station on the San Francisco Bay Area Rapid Transit system. The results demonstrate that, relative to the referent period (2000–2001): (a) the station-led house price impacts are spatially heterogeneous—the house price increased in one pocket only, comprising less than one-tenth of the dataset, not across the entire 0–2 mile station area, (b) the price increase in that pocket began right after the project announcement period, and (c) the price impacts indicated by the MGWR model markedly differ from baseline ordinary least square regression (OLS) estimates. Overall, the study’s findings highlight the need to move beyond average estimation techniques, such as OLS, to those that account for spatially heterogeneous price impacts, such as GWR and MGWR.

Urban Science doi: 10.3390/urbansci10080458

Authors: Sara Rosa Cristina Rakasi Inês Sousa Mariana Amaral Anabela Correia Martins

Background: To date, there are no known published studies in Portugal that link the perceived neighborhood walkability of a specific geographical area to the functional capacity and social participation of older adults living in the community. Thus, the main objective of this study, conducted in Portugal, is to examine whether the perceived neighborhood walkability is associated with functional capacity, walking confidence, social participation, and exercise self-efficacy among community-dwelling older adults, thereby contributing to the national evidence base on the influence of contextual factors on human functioning, with particular relevance to active and healthy aging. Methods: An exploratory, cross-sectional study was conducted using data from older adults (aged 50 and over) living in the community, in Portugal. A member of the research team assessed physical function using objective measures of upper and lower body function, balance and mobility. To assess the perceived neighborhood walkability, a validated questionnaire for Portuguese adults living in the community with good internal consistency (α = 0.848) was used. The walkability dimensions assessed were safety, facilities/surroundings, comfort/esthetics and accessibility/connectivity. The Pearson correlation coefficient was used to analyze the relationships between continuous variables. Differences between groups were analyzed using independent sample Student’s t-tests or analysis of variance (ANOVA) as appropriate. Results: Perceived neighborhood walkability was associated with several sociodemographic, health, and psychosocial variables. Higher educational levels and better self-perceived health were associated with more positive perceptions of walkability. Participants without urinary incontinence and osteoarthritis reported significantly higher walkability scores, particularly in the safety, facilities/surroundings, and comfort/esthetics dimensions. Older age was associated with higher scores in the facilities/surroundings dimension, whereas slower gait speed and higher anxiety levels were associated with lower perceptions in this dimension. Few significant associations were found between perceived neighborhood walkability and objective physical function measures, and these associations were generally weak. Conclusions: Overall, the findings suggest that neighborhood walkability is a multidimensional construct influenced not only by environmental characteristics but also by health status, psychological factors, and individual perceptions. These results reinforce the importance of considering contextual and environmental factors when promoting mobility, participation, and healthy aging among community-dwelling older adults.

Urban Science doi: 10.3390/urbansci10080456

Authors: Abigail Ortiz Curinambe Alvaro Adrian Pérez Sosa Vanessa Raymundo Elvira Ruiz Reyes Crayla Alfaro Cecilia Uribe Quiroz Gustavo Reyes Marilu Loera Paredes

The increase in global carbon dioxide emissions is intensifying climate change and severely affecting diverse communities. Addressing these impacts requires sustainable planning approaches that promote environmental and social balance. This research aims to develop a transferable planning methodology incorporating ex ante evaluation for sustainable productive rural settlements, the application of which is examined through a design proposal in Pocollay, Tacna, used as a case study. The methodology comprises six sequential phases: integrated territorial diagnosis, construction of the multicriteria evaluation model, assessment of the baseline scenario, formulation of the planning model, application of the methodology to the case study, and comparative multicriteria evaluation of the projected scenario. As an application of the methodology, a Master Plan and a productive housing module were developed, integrating the proposed planning principles within a circular economy approach, together with bioclimatic design strategies aimed at resource efficiency, passive comfort, water management, renewable energy integration, and reduced environmental pressure. Compared with the baseline scenario, the projected scenario obtained higher potential performance scores across the architectural, environmental, productive, and socioeconomic indicators evaluated. These results represent expected performance according to predefined criteria rather than impacts observed after construction. In conclusion, the main contribution of the research is the proposed planning and evaluation methodology, which can be replicated or adapted in future applications by recalibrating its indicators, weights, climatic parameters, productive systems, material strategies, and community priorities.

Urban Science doi: 10.3390/urbansci10080457

Authors: Lingguang Wang Changbo Kang Yanchen Qiu Yixuan Shang Xiaomeng Wang Qifeng Yu

Urban traffic systems are increasingly vulnerable to non-recurrent congestion and abnormal traffic fluctuations, posing significant challenges to intelligent traffic management and resilient transportation operations. Existing traffic anomaly detection methods often struggle to simultaneously characterize heterogeneous anomaly patterns under dynamically evolving traffic states, while severe class imbalance and limited data plausibility further constrain detection reliability. To address these challenges, this study proposes a traffic-prior-guided state-aware framework for robust urban traffic anomaly detection. A Multi-Scale Natural Neighborhood (MS-NaN) module transforms one-dimensional traffic flow sequences into a nine-dimensional representation integrating sequence dynamics, multiscale statistical deviations, and spatiotemporal phase characteristics, thereby embedding traffic state priors into the detection process. Building upon these representations, the Dual-Branch Context-Gated Network (DB-CGNet) separately captures instantaneous traffic disruptions and trend-evolving congestion patterns. An adaptive context-aware gated fusion mechanism then combines the branch features to enhance robustness under complex and non-stationary traffic conditions. To improve evaluation realism, high-fidelity baseline traffic data are generated through B-spline smoothing and first-order autoregressive residual modeling, and anomaly patterns are constructed under Highway Capacity Manual (HCM)-constrained capacity reduction mechanisms. Experiments conducted on a 91-day urban expressway dataset demonstrate that the proposed method achieves the best overall performance among eight benchmark models under a 72 min observation window, attaining an F1-score of 0.7757 and an area under the receiver operating characteristic curve (AUC) of 0.9112. Ablation studies further reveal the critical role of traffic prior features in detecting short-duration evolving anomalies. The proposed framework provides a robust and interpretable solution for intelligent urban traffic monitoring, anomaly warning, and resilient traffic operation management.

Urban Science doi: 10.3390/urbansci10080455

Authors: Claudia González-Roldán Fabián Díaz-Muñoz

Public spaces are essential for urban well-being, social interaction, environmental quality, and territorial equity; however, their presence does not necessarily ensure adequate quality, accessibility, or multifunctionality. Although previous research has emphasized the importance of green and public spaces, fewer studies have integrated multidimensional quality assessment, GIS-based spatial analysis, and multicriteria prioritization in intermediate Latin American cities. This study aimed to evaluate spatial inequalities in the quality of urban public spaces in Loja, Ecuador, through a GIS-based multi-attribute composite index. A total of 183 public spaces were assessed using structured field observation of observable conditions and organized into six dimensions: functional, environmental, cultural, recreational, safety, and economic. The data were cleaned, validated, integrated with spatial layers, and analyzed through descriptive, inferential, multivariate, spatial autocorrelation, and multicriteria procedures. The results showed that public space quality was mainly concentrated at low and medium levels, with functional and safety dimensions playing a stronger role in the global index, while cultural, recreational, and economic components showed weaker performance. Spatial analysis revealed significant territorial differences, local clusters, and spatial outliers. The proposed framework provides a replicable tool to diagnose observable public space quality, identify priority intervention areas, and support evidence-based urban planning in other intermediate cities.

Urban Science doi: 10.3390/urbansci10080454

Authors: Xinyan Chen Domenico Chizzoniti Tommaso Lolli

Rapid globalization has caused the architectural and urban homogenization phenomenon, weakening regional characteristics and architectural and urban identity, especially in many historic cities. To address this phenomenon, this paper explores how urban dwellers perceive these processes, offering a user-centered perspective. The research mainly uses a questionnaire-based survey and selects Hangzhou, China, as the research site. It distributed 500 questionnaires and obtained 435 responses, of which 413 valid adult responses were included in the final analysis. Applying both quantitative and qualitative approaches, the research focuses on two phases: the first phase’s results show that the dwellers primarily identify architectural identity through architectural characteristics and daily spatial experiences, while their dissatisfaction with contemporary architecture is mainly based on cultural disconnect, disharmony with the surrounding environment, and formalism. They prefer architecture that can inherit traditional and local characteristics while offering new interpretations and expressions in the contemporary context. Grounded in this questionnaire evidence, the second phase concentrates on translating these perceptions into design insights and approaches, which are as follows: integrate tradition into the design semantics and concepts; reinterpret traditional spatial composition and reasonably insert formal innovations consistent with the local context; incorporate the use of traditional materials and construction; and enhance the connection between the architecture and the surrounding environment and urban tissue. The paper not only expands the discipline and relevant theories but also provides a user-centered, replicable framework for architectural and urban design that strengthens the regionally specific architectural and urban identity to respond to the challenges of homogenization.

Urban Science doi: 10.3390/urbansci10080453

Authors: Raúl Sánchez-Francés Carolina Martínez-Ruiz Esther San José Bárbara Díez José María Sanz Jorge Calvo Silvia Gómez Laura Wendling Juan García-Duro

Urbanisation and climate change have intensified the Urban Heat Island (UHI) effect in European cities, increasing thermal stress and health risks, especially for vulnerable people. Nature-based Solutions (NbS), such as green infrastructures (GI), offer effective mitigation strategies. A notable example is the Horizon 2020 URBAN GreenUP project in Valladolid, Spain, where a green shade shelter infrastructure was installed and monitored between 2019 and 2022 to evaluate its cooling performance and its effects on temperature-based urban heat indicators through the use of Key Performance Indicators (KPIs). Local thermal conditions were monitored across two adjacent narrow streets—one with the green shade shelter and one as a control. The installation of the green shade shelter in Valladolid produced measurable thermal benefits. During summer peaks, it reduced ambient temperatures by approximately 0.9 °C, with daily maximum temperatures decreasing by 1.0–3.0 °C. In winter, daily minimum temperatures dropped by around 1.0 °C, while autumn saw an increase of 0.7 °C. Summer minimum temperatures varied, ranging from a 0.2 °C decrease in early summer to a 0.7 °C increase in late summer, with a 0.3 °C rise during peak summer in mid-July. The intervention also reduced the frequency and delayed the onset of days exceeding 35 °C and nights above 20 °C, although the delay in peak tropical nights was limited to seven days. These findings indicate that green shade shelters can contribute to improving street-level thermal conditions and reducing temperature-based heat exposure indicators in dense urban environments.

Urban Science doi: 10.3390/urbansci10080452

Authors: Stefan Milojević Snežana Knežević Miroslav Knežević Aleksandra Vujko

Urban competitiveness has traditionally been associated with infrastructure, economic performance, and innovation capacity, while the role of financial governance has received considerably less attention. This study examines how citizens form perceptions of urban financial integrity and whether such perceptions influence evaluations of urban attractiveness. Drawing on a governance-based framework, the study investigates the relationships among Digital Governance, Financial Transparency, Anti-Fraud Capacity, Financial Integrity, and Urban Attractiveness. Data were collected from 2764 residents of 18 digitally advanced cities across Northern and Western Europe and North America. To enhance methodological rigor, the sample was randomly divided into two equal subsamples and analyzed using Exploratory Factor Analysis, Confirmatory Factor Analysis, and Structural Equation Modeling. The results indicate that Digital Governance is positively associated with both Financial Transparency and Anti-Fraud Capacity, while Financial Transparency and Anti-Fraud Capacity are positively associated with stronger perceptions of Financial Integrity. Financial Integrity emerged as a significant predictor of Urban Attractiveness and served as the principal mechanism through which governance practices influenced broader evaluations of cities. The findings suggest that citizens do not perceive cities as attractive simply because they are digitally advanced; rather, digital governance becomes valuable when it enhances confidence that public financial resources are managed transparently, responsibly, and in the public interest. These results identify Financial Integrity as the key mechanism through which citizens translate governance quality into perceptions of urban attractiveness.

Urban Science doi: 10.3390/urbansci10080451

Authors: Tamás Köpeczi-Bócz

Smart city and smart region governance increasingly relies on data-informed decision-making, stakeholder participation, digital tools, and public feedback. However, these mechanisms do not automatically create institutional learning. This article examines sustainable smart region governance as an institutional learnability problem and asks whether participation, local knowledge, and feedback are converted into adaptive action and retained as institutional memory. The study applies a Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR)-informed structured evidence mapping combined with an embedded regional case diagnosis from the Tokaj Wine Region, Hungary. The analysis integrates the literature on smart governance, learning regions, higher education quality assurance, territorial resilience, and adaptive governance with regional governance observation materials, stakeholder survey data, coding tables, calculation workbooks, and analytical figures deposited in a public Figshare dataset. The results identify the Act/Remember gap as the central learning-cycle disruption. Planning, implementation, monitoring, and consultation may be present, but feedback often fails to become adaptive action, and action is weakly retained as institutional memory. The comparison with higher education quality assurance shows that structured feedback and continuous improvement principles are transferable only as learning logic, not as procedural models. The findings also show that single-profile territories are especially vulnerable to delayed learning, strategic lock-in, and weak community knowledge-building. The article contributes to smart governance research by proposing institutional learnability as a diagnostic capacity of sustainable smart regions. It argues that digital tools should function as learning infrastructure supporting traceability, feedback-to-action mechanisms, and institutional memory, rather than as substitutes for human deliberation, trust, and collective responsibility.

Urban Science doi: 10.3390/urbansci10080450

Authors: Marcel Bartumeu Ramentol Parfait Atchade-Adelomou Adrian Mora-Carrero Kent Larson Luis Alonso-Pastor Marta Domenech

Planning long-term national development under uncertainty is difficult for small states, where indicators are fragmented, frequently revised, and span tightly coupled social, economic, and environmental domains. Scenario tools can support such decisions without committing to a single forecast, but they often lack historical grounding, cross-domain consistency, reproducible update pipelines, and explicit links between policy choices and outcomes. We present the Andorra Scenario Engine, a transparent, data-grounded framework that harmonizes multi-source national indicators into a consistent state vector and propagates four contrasting pathways—Continuity, Overgrowth, Degrowth, and Density—to 2049 through bounded, coupled update rules. The engine belongs to the exploratory-modelling tradition: an upstream, auditable layer toward a national digital twin rather than a forecasting system, whose outputs are internally consistent conditional futures. A central structural modelling choice is to derive population endogenously from GDP growth via a lagged labour-immigration elasticity (0.40 at a one-year lag, 0.10 at two years), grounded in IMF (2025) and World Bank data. A back-cast benchmark quantifies the accuracy cost of this choice (9.5% population RMSE against 1.7% for a linear trend), accepted in exchange for a policy-relevant causal lever. Three macroeconomic parameters and a housing-affordability anchor are calibrated to 2010–2024 official statistics (Nelder–Mead; RMSE = 1.77% on real GDP per capita). Scenario endpoints for 2049 range from 70,049 (Degrowth) to 174,002 (Overgrowth); a sensitivity audit identifies the housing-affordability threshold and the lag-1 elasticity as the load-bearing assumptions on which the headline signals depend. The framework provides a reproducible, human-in-the-loop baseline for comparing policy-relevant trade-offs and binding constraints in data-scarce microstates.

Urban Science doi: 10.3390/urbansci10080449

Authors: Patcha Siwapornpitak Napat Harnpornchai

Economic development is multidimensional, yet provincial comparisons in Thailand often rely on individual indicators or broad sustainability indices. This study constructs separate TOPSIS rankings of economic prosperity and distributional outcomes for all 77 Thai provinces. Six prosperity indicators capture economic output, human capital, spatial agglomeration, labor market outcomes, and structural transformation, while four distributional indicators capture income inequality, economic vulnerability, informal employment, and household dependency. The analysis uses 2024 provincial accounts and Labor Force Survey microdata, with comparisons for 2022–2024. Prosperity is concentrated in Bangkok, the surrounding metropolitan region, and the Eastern Seaboard, while Phuket represents a distinct tourism-led pathway. Favorable distributional outcomes are concentrated within the metropolitan–industrial corridor, whereas disadvantage is more prevalent in the North and Northeast. The rankings are associated but conceptually distinct, and the prosperity ranking differs meaningfully from one based solely on GPP per capita. The prosperity ranking is highly stable over time, while the distributional ranking exhibits substantial stability after harmonizing income coverage. Both rankings are robust to alternative normalization procedures, weighting schemes, and aggregation methods. Spatial statistics confirm clustering. The findings demonstrate the value of separating economic prosperity from distributional disadvantage when benchmarking provincial development and assessing urban–regional disparities.

Urban Science doi: 10.3390/urbansci10080448

Authors: Saif Ul Haq Muhammad Iqbal Musaddaq Azeem Muhammad Mohsin Rashid Muhammad Kashif

This study aims to examine the role of Relational Stakeholder Management (RSM) on the success of sustainable construction projects in urban areas of Pakistan. The study also examines the mediating role of trust (competence trust, integrity trust, and intuitive trust) and the moderating role of project managers’ leadership skills. Data were collected from 303 professionals working on sustainable construction projects in Pakistan and analyzed using Structural Equation Modeling (SEM). The results show that RSM has a positive and significant direct impact on the success of sustainable construction projects, while competence trust and integrity trust mediate this relationship. However, Intuitive Trust did not mediate the relationship between RSM and project success. Furthermore, the project manager’s leadership competencies strengthen relationships with relational stakeholders and foster trust, thereby improving overall project success. This research highlights that, in addition to technical factors, human and relational aspects are crucial to the success of energy-efficient and low-carbon construction projects in urban areas of Pakistan. The study provides integrated empirical evidence on the interplay between stakeholder relationships, trust, and leadership, specifically in the context of sustainable construction projects in urban areas of Pakistan. The findings of the study provide practical insights to improve RSM, develop trust, and strengthen leadership competencies to enhance success in sustainable construction projects.

Urban Science doi: 10.3390/urbansci10080447

Authors: Jiuxing Wu Fanfan Qian

Rapid urbanization can shrink and fragment cultivated land while raising agricultural productivity, creating mismatches among spatial configuration, functional performance, and management modes. These dimensions are rarely assessed in a unified, value-neutral framework. We developed a Spatial–Functional–Modal (SFM) framework to evaluate multidimensional synchronicity in 46 county-level units of the Nanjing Metropolitan Area, China, using Period 6 data spanning 2000–2022. We combined 18 entropy-weighted indicators with coupling and coupling coordination degree (CCD) models at county and municipal scales. Regional SFM-CCD rose from 0.304 to 0.327 but remained in the model-defined near-misalignment category, while average coupling declined from 0.747 to 0.740. All pairwise CCDs increased, but coupling trajectories differed: spatial–functional coupling weakened, spatial–modal coupling diverged between Jiangsu and Anhui, and functional–modal coupling strengthened. Anhui’s SFM-CCD increased more consistently and surpassed Jiangsu in later years. Nanjing remained a relative synchronicity trough, reflecting weaker alignment among normalized dimensions rather than lower absolute agricultural capacity. Alternative weights and ±10% and ±20% perturbations largely preserved relative rankings and the overall temporal pattern, but absolute values and categories remained method-sensitive. The framework diagnoses asynchronous transitions and can inform differentiated governance in other rapidly urbanizing regions.

Urban Science doi: 10.3390/urbansci10080446

Authors: Aleksandar Trifunović Ivan Ivanović Nenad Marković Zoran Vidović Tijana Ivanišević

The rapid transition toward electric mobility is widely recognized as a key strategy for improving urban environmental quality. However, while electric vehicles eliminate tailpipe emissions, they continue to contribute to environmental pressures through non-exhaust sources such as tire wear, road surface abrasion, and particle resuspension. This study develops a composite index framework for assessing road-segment-level operational environmental burdens associated with electric traffic, focusing on traffic operations, electric vehicle load characteristics, non-exhaust emission potential, and meteorological dispersion conditions. The framework does not constitute a life-cycle assessment and does not include battery production, electricity-generation mix, or other upstream environmental impacts. The framework combines four dimensions of influence: traffic operations, electric vehicle characteristics, non-exhaust emission processes, and meteorological dispersion conditions. Indicator selection was performed using the Delphi method, while indicator weights were determined through the Analytic Hierarchy Process (AHP). The methodological contribution lies not in the individual methods applied, but in their integration into a road-segment-level assessment framework specifically designed to identify and prioritize environmentally sensitive locations under traffic electrification scenarios. The resulting model incorporates sixteen indicators aggregated into a single environmental impact index that enables the ranking, classification, and prioritization of urban road segments according to their environmental burden. A case study conducted on selected urban streets demonstrates that non-exhaust emission indicators, particularly tire wear and particle resuspension, represent the most influential factors in the assessment process. Within the illustrative five-segment case study, the relative road-segment ranking remained unchanged under the electrified-traffic scenario, while the structure of the assessed burden shifted toward non-exhaust processes. The proposed framework provides a practical decision-support tool for urban planners and transport authorities by enabling the identification of environmentally sensitive locations, prioritization of infrastructure interventions, and support for sustainable mobility strategies in increasingly electrified urban transport systems.

Urban Science doi: 10.3390/urbansci10080445

Authors: Matej Cenky Jozef Bendik Peter Janiga

Freely accessible weather APIs are an attractive input for photovoltaic (PV) power prediction, yet how their reference-based error carries through—under temporal aggregation—into day-ahead PV energy is rarely quantified before model development. This study audits eight freely accessible weather-data services—seven forecast services and the Meteostat observational archive—and finds that, for the endpoints, subscription tiers, and collection period evaluated here, only two of the forecast services expose hourly global horizontal irradiance (GHI), while a third advertised irradiance field returns empty—itself a material result for municipal integrators. The two irradiance-capable services are propagated through a common physical PV model of the 548 kWp east–west rooftop plant being built on a university campus in Bratislava, Slovakia, against independent references (CAMS irradiance; NASA POWER temperature and wind). Throughout, “error” denotes discrepancy against the reference, not measurement truth. Over a common 62-day spring–summer window, the day-ahead daily-energy mean absolute error (MAE, relative to mean reference daily energy) is 10–11% for both sources; Open-Meteo’s winter-inclusive own window raises its value to about 13%. On the matched window, Open-Meteo has the lower hourly GHI RMSE (121 vs. 128 W·m−2), yet this advantage does not carry through to day-ahead energy—the point-estimate ordering even changes—and neither matched-window difference is statistically resolved. Because daily aggregation rewards low bias over low scatter, this ordering change is already present in daily GHI energy—before the PV conversion—so hourly irradiance accuracy alone does not determine day-ahead energy. Propagated input-data auditing is therefore an advisable step before ML-based PV forecasting and day-ahead scheduling of urban distributed PV.

Urban Science doi: 10.3390/urbansci10080444

Authors: Tamer ElSerafi

Smart mobility strategies often emphasize digital information, applications, and data-driven transport management, while giving less attention to the stop-level conditions that shape passengers’ everyday experience. This study develops and applies a Smart Bus Stop Readiness Index (SBSRI) to assess seven interchange bus stops in Jeddah, Saudi Arabia. The index integrates five weighted dimensions: Passenger Information and Digital Readiness; Physical and Thermal Comfort Provision; Pedestrian Accessibility and Universal Design; Safety and Security; and Land-Use and Activity Integration. Data were collected through field audits, spatial mapping, passenger observations, and a short survey of 71 users. The results indicate that the selected stops have operational interchange importance but generally limited readiness. The mean SBSRI score was 39.07/100; under the adopted planning-oriented classification scheme, only Al-Balad Main Station A achieved moderate readiness, while the remaining stops were classified as showing low or very low readiness. Physical and Thermal Comfort Provision was the weakest dimension, particularly in relation to shade, seating, shelter, and shaded waiting areas. Passenger information and pedestrian accessibility also showed substantial deficiencies. Sensitivity analysis indicated that the principal stop rankings remained stable under alternative weighting scenarios, although category labels were more responsive to threshold selection. This study concludes that smart bus stop readiness should be assessed as a socio-technical condition integrating digital systems with climate-responsive waiting provision, pedestrian accessibility, safety, and the surrounding urban context.

Urban Science doi: 10.3390/urbansci10080443

Authors: Angela Girardo Edmond Manahasa Odeta Manahasa Emina Zejnilović

This research examines the impact of urbicide on urban memory, using the city of Sarajevo as a case study. Urbicide is defined as the deliberate destruction of the built environment, including both its tangible and intangible aspects. This study proposes a place-based, multilayered methodological framework to analyze the effects of urbicide on the erasure of urban memory among inhabitants, as well as on traumatic and transformed urban memory. The methodological approach proposed and used in this research includes desk research; urban analysis to reveal the material evidence of destruction; sampling to categorize the level of destruction; visual documentation; surveying to measure the impact of urbicide on urban memory; thematic analysis to interpret the results; and mapping to locate both the tangible and intangible aspects of the survey results. The suggested methodological approach is tested through a pilot study in the city of Sarajevo, 31 years after the end of the 1992–95 siege. The results of the pilot survey presented in this paper, although partial due to the sample size, allowed us to explore the feasibility of the method and to implement the necessary improvements to measure the impacts of urbicide on city memory. Furthermore, the pilot study highlighted the need for a holistic, mixed-methods approach to investigate both the tangible and intangible aspects of urbicide, with a specific emphasis on the use of visual questionnaires.

Urban Science doi: 10.3390/urbansci10080442

Authors: Lasithasree Lakshmanan Sudhagar Nagarajan

Three-dimensional (3D) building reconstruction plays an important role in urban planning, disaster resilience, and sustainable infrastructure development. Conventional approaches based on airborne Light Detection and Ranging (LiDAR) data can be computationally intensive and often require large labeled datasets, particularly for large-scale applications. This study presents a semi-automated workflow for reconstructing multi-level 3D building models by integrating airborne LiDAR point cloud data with building footprints extracted from National Agriculture Imagery Program (NAIP) imagery using a Mask Region-Based Convolutional Neural Network (Mask R-CNN). The extracted footprints were used to spatially isolate building-specific LiDAR subsets for 3D reconstruction. The proposed methodology generated building models at multiple Levels of Detail (LOD), ranging from two-dimensional (2D) footprints to volumetric representations with detailed roof structures. Building footprint extraction was quantitatively evaluated against LiDAR-derived footprints generated using Density-Based Spatial Clustering of Applications with Noise (DBSCAN), which served as the reference dataset and detected buildings obscured by tree canopy. The reconstruction workflow was implemented in Open3D and incorporated a boundary-aware mesh refinement strategy based on ear-clipping triangulation to improve rooftop continuity in LOD2 models. The proposed footprint extraction framework achieved a mean Intersection over Union (IoU) of 0.8226 relative to LiDAR-derived reference building footprints, indicating reliable building delineation that supports the proposed multi-level 3D building reconstruction workflow.

Urban Science doi: 10.3390/urbansci10080441

Authors: Pawita Boonrat Voravika Wattanasoontorn

The management of municipal solid waste (MSW) in a region driven by tourism is a challenge. The dynamics of the waste produced can fluctuate significantly. Islands are particularly vulnerable due to geographic constraints and limited infrastructure. Using data to forecast and evaluate MSW management strategies would help make policy decisions. This research introduces a data-driven framework that integrates tourism dynamics with a predictive baseline for MSW generation and facilitates ongoing evaluation of system performance. The framework comprises four operational zones, namely data acquisition, baseline modelling, deviation analysis, and dashboard-based communication. It also follows the waste stream from upstream waste generation, through midstream collection and transfer, to downstream treatment and disposal. Phuket Island, Thailand, was chosen as a case study. The island has strong tourism-driven waste variability, limited waste management infrastructure, and a clear upstream–midstream–downstream waste-management chain. Tourism was explicitly integrated as an exogenous factor to capture transient demand effects. The amount of MSW was modelled using monthly tourism data. Support Vector Regression was selected to establish the expected waste baseline owing to its high predictive accuracy (MAE = 1143 t, RMSE = 1352 t and MAPE = 3.3%) outperforming other tested models (i.e., SARIMAX, Mean Baseline, Seasonal Naive, Random Forest and Histogram-Based Gradient Boost). Then, it was used to establish the baseline under normal conditions. The residual was then calculated as the difference between the observed values, and the performance of the maintenance system can be further assessed using the deviation analysis. A normal range defined within 3σ of the residual percentages from a baseline; values outside this range are flagged as anomalies. The results were integrated into a prototype dashboard to support operational monitoring, policy evaluation, and stakeholder-orientated interpretation. The proposed framework provides a practical basis for an evidence-based adaptive policy in tourism-dependent regions. Future work should incorporate waste composition and spatially explicit data to further improve the MSW management protocol. Considering that tourism demand exhibits seasonal patterns influenced by external factors, the results of this research offer an invaluable tool for waste management.

Urban Science doi: 10.3390/urbansci10080440

Authors: José Rojas-Quiroz Carlos Marmolejo-Duarte

Machine learning (ML) models like XGBoost have gained traction in housing valuation as they outperform classical hedonic models in predictive accuracy. However, their black box nature has limited their interpretability, until recent advances like SHAP values enabled deeper insights into variable contributions. This study explores whether XGBoost not only predicts housing prices more accurately but can also help identify latent submarket structures, without imposing predefined spatial or socioeconomic boundaries. Using a raw dataset of 7092 housing listings from Barcelona (reduced to 6527 unique listings and finally to 6112 observations after outlier removal), we employ a sequential methodological framework: first, OLS and Spatial Durbin Models identify statistically significant predictors while accounting for spatial dependence; second, an XGBoost model is trained with these validated variables to extract SHAP values quantifying each attribute’s model-attributed contribution to individual predicted prices; third, clustering these SHAP values reveals three distinct submarkets with systematic differences in model-attributed valuation patterns. We validate the resulting segments through five complementary procedures: out-of-sample cluster assignment verifying segment generalizability; nested OLS interaction models that formally test differences in model-attributed valuation patterns across clusters; spatial block bootstrap resampling that assesses cluster stability under geographic subsampling; non-parametric tests against the 2017 cadastral value—an independent administrative proxy for spatial value stratification; and spatial autocorrelation statistics confirming non-random geographic structure. Together, this multi-pronged validation provides convergent evidence that the identified segments capture stable and externally coherent patterns in the model’s learned valuation structure. Unlike prior studies focused solely on prediction, our approach bridges ML’s technical rigor with econometric interpretability. We argue that this capability may stem from XGBoost’s tree-based architecture, which naturally partitions the feature space to accommodate heterogeneous valuation patterns. Future research could extend this framework to more recent tree-based models, further advancing interpretable ML for housing market analysis.

Urban Science doi: 10.3390/urbansci10080439

Authors: Ravish Dubey Simone Mora Carlo Ratti

Urban areas contribute a dominant share of global carbon dioxide (CO2) emissions, yet city-scale emission estimates remain highly uncertain due to the limited spatial and temporal resolution of existing observation methods. This review paper examined the potential of horizontally scanning Differential Absorption LiDAR (DIAL) systems to address these gaps in urban CO2 monitoring. We reviewed current top-down and bottom-up approaches, identified their limitations in resolving intra-urban variability, and outlined a conceptual framework for deploying compact, eye-safe CO2 DIAL systems on elevated urban structures. We reviewed methods that combined horizontal CO2 scanning with wind measurements to enable high-resolution mapping of CO2 distributions, assessment of boundary-layer effects, and estimation of urban carbon fluxes using established mass-balance and inversion techniques. Conceptual deployment scenarios, illustrated using Boston as an example, demonstrated how a single elevated LiDAR unit could provide near-city-wide coverage and capture neighborhood-scale emission patterns. We further discussed calibration strategies, safety considerations, and integration with existing sensor networks and column observations. This review concluded horizontal CO2 LiDAR represents a promising pathway toward high-resolution, observation-based urban carbon monitoring, offering a complementary tool to existing methods and supporting future efforts to verify emission inventories, evaluate mitigation policies, and advance city-scale carbon management.

Urban Science doi: 10.3390/urbansci10080438

Authors: Yanelba E. Abreu-Rojas Juan C. Sala-Rosario Antonio Torres-Valle Antonio Jurado-Málaga Ulises J. Jauregui-Haza

Disaster risk perception in informal urban settlements remains insufficiently understood despite its importance for climate adaptation and urban resilience policies. This study evaluated disaster risk perception among residents of nine informal settlements in Greater Santo Domingo, Dominican Republic, focusing on the relationship between the subjective risk of disaster, poverty, and socio-environmental vulnerability. A mixed-methods approach was applied using the RISKPERCEP algorithm and a structured survey composed of 98 questions grouped into key perception variables. A total of 198 surveys were conducted across four municipalities, supported by expert consultation, probabilistic sample-size calculation, and statistical analyses including chi-square tests and Cramér’s V coefficients. The results revealed a generalized moderate underestimation of climate-related risks, mainly associated with limited understanding of hazards, weak institutional trust, low personal involvement, poor memory of past disasters, and reduced concern about consequences. Socioeconomic deprivation, particularly among women, retirees, and low-income groups, was strongly associated with higher perceived vulnerability. Statistical analyses demonstrated a dense and multidimensional network of interdependent social, economic, and spatial variables shaping vulnerability. The study concludes that low disaster risk perception constitutes a major barrier to climate adaptation in informal settlements and highlights the need for integrated public policies combining social protection, climate education, urban resilience, and community-based adaptation strategies. The implications of this study point to the use of a disaster risk perception inquiry method at the community level, structured around specific variables that allow the identification of underlying causes of the widespread underestimation of disaster risk. This approach enables the design of adaptive policies—both structural and non-structural—that explicitly incorporate these aspects when formulating resilience measures. Future research should aim to generalize the study to other communities across the country, preceded by addressing the limitations identified.

Urban Science doi: 10.3390/urbansci10080437

Authors: Vlad Stoicescu Daniela Ioana Manea Vasile Alecsandru Strat Răzvan Popescu Alina-Cornelia Luchian (Chiriac) Radu Moldoveanu Alexandra Stefan

European smart cities face a distinct decarbonisation challenge in the gas component of urban energy consumption, which cannot be addressed through internal optimisation alone. The European Union (EU) Mission for Climate-Neutral and Smart Cities selected 112 cities for climate neutrality by 2030, including Bucharest Sector 2, Cluj-Napoca, and Suceava in Romania. The Mission timeline coincides with the Russian pipeline gas phase-out under Regulation (EU) 2026/261, the 5 August 2026 transposition deadline for the Hydrogen and Decarbonised Gas Market Package (also referred to as the Fourth Gas Package), and the post-Hormuz energy market environment of 2026. This paper develops a hinterland framework that links Romanian Mission cities to their rural renewable gas supply through biomethane and renewable hydrogen production, integrated with circular bioeconomy strategies and routed through the national transmission system operated by Transgaz. The empirical analysis combines documentary evidence from the May 2026 consultation on Government Emergency Ordinance 9/2026, institutional documentation of Transgaz and Romgaz, and the comparative European literature on smart city renewable energy integration. Findings show that Mission city decarbonisation pathways depend on rural-to-urban gas infrastructure calibration under the post-2024 regulatory cascade. The paper proposes specific deployment strategies for each Romanian Mission city.

Urban Science doi: 10.3390/urbansci10080436

Authors: Balbine Alindekon Bopaki Phogole Kowiyou Yessoufou

Urban Heat Island (UHI) effects are increasingly acknowledged as a critical urban climate challenge with far-reaching consequences for human health and overall well-being. However, the conceptual structure, temporal evolution, and intellectual landscape of studies examining the relationships between UHI and human well-being remain fragmented, thereby constraining the development of integrated knowledge frameworks needed to guide future research, urban adaptation strategies, and evidence-based policy interventions. To this end, a total of 4857 studies were retrieved from the Scopus and Web of Science databases and screened following the PRISMA guidelines. These studies were then analyzed using Bibliometrix and VOSviewer. The results reveal a rapid and exponential growth in scientific output, particularly after 2010, with the output reaching its highest level in recent years. These outputs were shaped mostly in China and the United States with a well-established international collaboration network, while the Global South remain significantly underrepresented in scientific productions. We also found that studies are primarily structured around four dominant research clusters: urban heat island, thermal comfort, land surface temperature, and climate change. Furthermore, early studies predominantly focused on urban surface properties and built-environment characteristics, while recent research has increasingly shifted toward human health impacts, thermal stress, heat vulnerability, and well-being. Emerging research directions further highlight growing interest in nature-based solutions for mitigating UHI effects, alongside the application of advanced technologies such as machine learning and remote sensing for high-resolution urban climate assessment. Overall, our findings indicate a transition toward a more integrated urban climate–health–well-being research framework, while simultaneously revealing persistent geographical and conceptual gaps, particularly across the Global South. We therefore advocate for increased empirical research, stronger international collaboration, and context-specific urban adaptation strategies to better safeguard human well-being under intensifying urban heat conditions.